^(99m)TC-Methylene diphosphonate uptake at injury site correlates with osteoblast differentiation and mineralization during bone healing in mice

99mTc-Methylene diphosphonate （99mTc-MDP） is widely used in clinical settings to detect bone abnormalities. However, the mechanism of 99mTc-MDP uptake in bone is not well elucidated. In this study, we utilized a mouse tibia injury model, single-photon emission computed tomography （gamma scintigraphy or SPECT）, ex vivo micro-computed tomography, and histology to monitor 99mTc-MDP uptake in injury sites during skeletal healing. In an ex vivo culture system, calvarial cells were differentiated into osteoblasts with osteogenic medium, pulsed with 99mTc-MDP at different time points, and quantitated for 99mTc-MDP uptake with a gamma counter. We demonstrated that 99mTc-MDP uptake in the injury sites corresponded to osteoblast generation in those sites throughout the healing process. The 99mTc-MDP uptake within the injury sites peaked on day 7 post-injury, while the injury sites were occupied by mature osteoblasts also starting from day 7. ~mTc-MDP uptake started to decrease 14 days post-surgery, when we observed the highest level of bony tissue in the injury sites. We also found that 99mTc-MDP uptake was associated with osteoblast maturation and mineralization in vitro. This study provides direct and biological evidence for 99mTc-MDP uptake in osteoblasts during bone healing in vivo and in vitro.

Correlated Differential Privacy of Multiparty Data Release in Machine Learning

Differential privacy(DP)is widely employed for the private data release in the single-party scenario.Data utility could be degraded with noise generated by ubiquitous data correlation,and it is often addressed by sensitivity reduction with correlation analysis.However,increasing multiparty data release applications present new challenges for existing methods.In this paper,we propose a novel correlated differential privacy of the multiparty data release(MP-CRDP).It effectively reduces the merged dataset's dimensionality and correlated sensitivity in two steps to optimize the utility.We also propose a multiparty correlation analysis technique.Based on the prior knowledge of multiparty data,a more reasonable and rigorous standard is designed to measure the correlated degree,reducing correlated sensitivity,and thus improve the data utility.Moreover,by adding noise to the weights of machine learning algorithms and query noise to the release data,MP-CRDP provides the release technology for both low-noise private data and private machine learning algorithms.Comprehensive experiments demonstrate the effectiveness and practicability of the proposed method on the utilized Adult and Breast Cancer datasets.

A novel satellite-equipped receiver for autonomous monitoring of GNSS navigation signal quality

Global navigation satellite system(GNSS) comes with potential unavoidable application risks such as the sudden distortion or failure of navigation signals because its satellites are generally operated until failure. In order to solve the problems associated with these risks, receiver autonomous integrity monitoring(RAIM) and ground-based signal quality monitoring stations are widely used. Although these technologies can protect the user from the risks, they are expensive and have limited region coverage. Autonomous monitoring of satellite signal quality is an effective method to eliminate these shortcomings of the RAIM and ground-based signal quality monitoring stations; thus, a new navigation signal quality monitoring receiver which can be equipped on the satellite platform of GNSS is proposed in this paper. Because this satellite-equipped receiver is tightly coupled with navigation payload, the system architecture and its preliminary design procedure are first introduced. In theory, code-tracking loop is able to provide accurate time delay estimation of received signals. However, because of the nonlinear characteristics of the navigation payload, the traditional code-tracking loop introduces errors. To eliminate these errors, the dummy massive parallel correlators(DMPC) technique is proposed. This technique can reconstruct the cross correlation function of a navigation signal with a high code phase resolution. Combining the DMPC and direct radio frequency(RF) sampling technology, the satellite-equipped receiver can calibrate the differential code bias(DCB) accurately. In the meantime, the abnormities and failures of navigation signal can also be monitored. Finally, the accuracy of DCB calibration and the performance of fault monitoring have been verified by practical test data and numerical simulation data, respectively. The results show that the accuracy of DCB calibration is less than 0.1 ns and the novel satellite-equipped receiver can monitor the signal quality effectively.