27 research outputs found
Sost haploinsufficiency provokes peracute lethal cardiac tamponade without rescuing the osteopenia in a mouse model of excess glucocorticoids
Glucocorticoid-induced secondary osteoporosis is the most predictable side-effect of this anti-inflammatory. One of the main mechanisms by which glucocorticoids achieve such deleterious outcome in bone is by antagonizing Wnt/β-catenin signalling. Sclerostin, encoded by Sost gene, is the main negative regulator of the pro-formative and anti-resorptive role of the Wnt signaling pathway in the skeleton. We hypothesized that the partial inactivation of sclerostin function by genetic manipulation will rescue the osteopenia induced by high endogenous glucocorticoid levels. Sost-deficient mice were crossed with an established mouse model of excess glucocorticoids and the effects on bone mass and structure were evaluated. Sost haploinsufficiency did not rescue the low bone mass induced by high glucocorticoids. Intriguingly, the critical manifestation of Sost-deficiency combined with glucocorticoid excess was sporadic, sudden, unprovoked, and non-convulsive death. Detailed histopathological analysis in a wide range of tissues identified peracute haemopericardium and cardiac tamponade to be the cause. These preclinical studies reveal outcomes with direct relevance to ongoing clinical trials exploring the use of anti-sclerostin antibodies as a treatment for osteoporosis. They particularly highlight a potential for increased cardiovascular risk and may inform improved stratification of patients that might otherwise benefit from anti-sclerostin antibody treatment
Chronic administration of Glucagon-like peptide-1 receptor agonists improves trabecular bone mass and architecture in ovariectomised mice
Some anti-diabetic therapies can have adverse effects on bone health and increase fracture risk. In this study, we tested the skeletal effects of chronic administration of two Glucagon-like peptide-1 receptor agonists (GLP-1RA), increasingly used for type 2 diabetes treatment, in a model of osteoporosis associated bone loss and examined the expression and activation of GLP-1R in bone cells. Mice were ovariectomised (OVX) to induce bone loss and four weeks later they were treated with Liraglutide (LIR) 0.3 mg/kg/day, Exenatide (Ex-4) 10 μg/kg/day or saline for four weeks. Mice were injected with calcein and alizarin red prior to euthanasia, to label bone-mineralising surfaces. Tibial micro-architecture was determined by micro-CT and bone formation and resorption parameters measured by histomorphometric analysis. Serum was collected to measure calcitonin and sclerostin levels, inhibitors of bone resorption and formation, respectively. GLP-1R mRNA and protein expression were evaluated in the bone, bone marrow and bone cells using RT-PCR and immunohistochemistry. Primary osteoclasts and osteoblasts were cultured to evaluate the effect of GLP-1RA on bone resorption and formation in vitro. GLP-1RA significantly increased trabecular bone mass, connectivity and structure parameters but had no effect on cortical bone. There was no effect of GLP-1RA on bone formation in vivo but an increase in osteoclast number and osteoclast surfaces was observed with Ex-4. GLP-1R was expressed in bone marrow cells, primary osteoclasts and osteoblasts and in late osteocytic cell line. Both Ex-4 and LIR stimulated osteoclastic differentiation in vitro but slightly reduced the area resorbed per osteoclast. They had no effect on bone nodule formation in vitro. Serum calcitonin levels were increased and sclerostin levels decreased by Ex-4 but not by LIR. Thus, GLP-1RA can have beneficial effects on bone and the expression of GLP-1R in bone cells may imply that these effects are exerted directly on the tissue
Distributed Localization in Censored Wireless Sensor Networks with Binary Data
In this paper we investigate distributed localization of an intruder in wireless sensor networks (WSNs), in which the
sensor nodes (SNs) censor their transmission to the fusion center (FC). The SNs locally detect the intruder and send their decision only if it is positive. The FC, on the other hand, uses those binary data to localize the intruder. We present the censored maximum likelihood (cML) localization algorithm, Furthermore, we derive two computationally simple localization algorithms, the quadratic approximate ML (QAML) and the linear approximate ML (LAML). The performance of the ML-based algorithms significantly outperforms the heuristics-based algorithms, such as the centroid method (CM) and the center of maximum enclosing rectangle (CMER), as the simulation results show
Low complexity and high accuracy angle of arrival estimation using eigenvalue decomposition with extension to 2D AOA and power estimation
Optimal Linear Fusion Rule for Distributed Detection in Clustered Wireless Sensor Networks
In this paper we consider the distributed detection of intruders in clustered wireless sensor networks (WSNs). The WSN is modelled by a homogeneous Poisson point process (PPP). The sensor nodes (SNs) compute local decisions about the intruder's presence and send them to the cluster heads (CHs). Hence, the CHs collect the number of detecting SNs in the cluster. The fusion center (FC), on the other hand, combines the the CH's data in order to reach a global detection decision. We propose an optimal cluster-based linear fusion (OCLR), in which the CHs' data are linearly fused. Interestingly, the OCLR performance is very close to the optimal clustered fusion rule (OCR) previously proposed in literature. Furthermore, the OCLR performance approaches the optimal Chair-Varshney fusion rule as the number of SNs increases
Non-line of Sight Error Mitigation in Ultra-wideband Ranging Systems Using Biased Kalman Filtering
[[abstract]]In this paper, a non-line of sight (NLOS) error mitigation method based on biased Kalman filtering for ultra-wideband (UWB) ranging is proposed. The NLOS effect on the measures of signal arrival time is considered one of the major error sources in range estimation and time-based wireless location systems. An improved biased Kalman filtering system, incorporated with sliding-window data smoothing and hypothesis test, is used for NLOS identification and error mitigation. Based on the results of hypothesis test, the estimated ranges are either calculated by smoothing the measured range when line of sight (LOS) status is detected, or obtained by conducting error mitigation on the NLOS corrupted measured range when NLOS status is detected. The effectiveness of the proposed scheme in mitigating errors during the LOS-to-NLOS and NLOS-to-LOS transitions is discussed. Improved NLOS identification and mitigation during the NLOS/LOS variations of channel status are attained by an adaptive variance-adjusting scheme in the biased filter. Simulation results show that the UWB channel status and the transition between NLOS and LOS can be identified promptly by the proposed scheme. The estimated time-based location metrics can be used for achieving higher accuracy in location estimation and target tracking