A 2-DOF drag-free control ground simulation system based on Stewart platform.

Space-based gravitational wave detection missions use multiple satellites to form a very large scale Michelson laser interferometer in space. This requires extremely high precision displacement measurements at the picometer level between test masses even millions of kilometers apart. Drag-free control is a key technology to ensure the ultra-static and ultra-stable space experiment platform for space-based gravitational wave detection. This paper proposes an innovative ground simulation scheme for drag-free control principle based on the Stewart platform. The kinematics and dynamics modeling of the Stewart platform used in the experiment is presented. A drag-free ground simulation experimental equipment is designed and built. A two-degree-of-freedom (2-DOF) drag-free controller is designed based on the H∞ loop shaping algorithm which outperforms a PID controller in Simulink simulation. A semi-physical simulation experiment is conducted to verify the controller designed using rapid control prototyping technology. The experimental results show that the control performance reaches the limit accuracy of the hardware device, thus verifying the effectiveness of the drag-free control algorithm.

Long non-coding RNA APDC plays important regulatory roles in metabolism of bone and adipose tissues.

The long noncoding RNA (lncR) ANRIL in the human genome is an established genetic risk factor for atherosclerosis, periodontitis, diabetes, and cancer. However, the regulatory role of lncR-ANRIL in bone and adipose tissue metabolism remains unclear. To elucidate the function of lncRNA ANRIL in a mouse model, we investigated its ortholog, AK148321 (referred to as lncR-APDC), located on chr4 of the mouse genome, which is hypothesized to have similar biological functions to ANRIL. We initially revealed that lncR-APDC in mouse bone marrow cells (BMSCs) and lncR-ANRIL in human osteoblasts (hFOBs) are both increased during early osteogenesis. Subsequently, we examined the osteogenesis, adipogenesis, osteoclastogenesis function with lncR-APDC deletion/overexpression cell models. In vivo, we compared the phenotypic differences in bone and adipose tissue between APDC-KO and wild-type mice. Our findings demonstrated that lncR-APDC deficiency impaired osteogenesis while promoting adipogenesis and osteoclastogenesis. Conversely, the overexpression of lncR-APDC stimulated osteogenesis, but impaired adipogenesis and osteoclastogenesis. Furthermore, KDM6B was downregulated with lncR-APDC deficiency and upregulated with overexpression. Through binding-site analysis, we identified miR-99a as a potential target of lncR-APDC. The results suggest that lncR-APDC exerts its osteogenic function via miR-99a/KDM6B/Hox pathways. Additionally, osteoclasto-osteogenic imbalance was mediated by lncR-APDC through MAPK/p38 and TLR4/MyD88 activation. These findings highlight the pivotal role of lncR-APDC as a key regulator in bone and fat tissue metabolism. It shows potential therapeutic for addressing imbalances in osteogenesis, adipogenesis, and osteoclastogenesis.

A Novel Closed-Loop Structure for Drag-Free Control Systems with ESKF and LQR.

Space-borne gravitational wave detection satellite confronts many uncertain perturbations, such as solar pressure, dilute atmospheric drag, etc. To realize an ultra-static and ultra-stable inertial benchmark achieved by a test-mass (TM) being free to move inside a spacecraft (S/C), the drag-free control system of S/C requires super high steady-state accuracies and dynamic performances. The Active Disturbance Rejection Control (ADRC) technique has a certain capability in solving problems with common perturbations, while there is still room for optimization in dealing with the complicated drag-free control problem. When faced with complex noises, the steady-state accuracy of the traditional control method is not good enough and the convergence speed of regulating process is not fast enough. In this paper, the optimized Active Disturbance Rejection Control technique is applied. With the extended state Kalman filter (ESKF) estimating the states and disturbances in real time, a novel closed-loop control structure is designed by combining the linear quadratic regulator (LQR) and ESKF, which can satisfy the design targets competently. The comparative analysis and simulation results show that the LQR controller designed in this paper has a faster response and a higher accuracy compared with the traditional nonlinear state error feedback (NSEF), which uses a deformation of weighting components of classical PID. The new drag-free control structure proposed in the paper can be used in future gravitational wave detection satellites.

Ferroptosis promotes anti-tumor immune response by inducing immunogenic exposure in HNSCC.

Accumulated evidence indicates that immune cell populations play pivotal roles in the process of tumor initiation, progression, recurrence, metastasis, and immune escape. Ferroptosis is a form of regulating cell death in the nexus between metabolism, redox biology, and human health. Ferroptosis is considered as a vital important event in HNSCC, but the underling mechanism of regulating immune cell populations remains poorly understood. Our tissue microarray study showed that patients with high expression of GPX4 were related to poor survival. Moreover, the expression of GPX4 has been negatively associated with immunogenic cell death-related protein calreticulin in HNSCC tissue cohort. Further, RSL3 was used to induce ferroptosis in HNSCC xenograft of C3H/He mouse. We found that the occurrence of ferroptosis had significantly reduced the number of myeloid-derived suppressor cells (MDSCs) and tumor-associated M2-like macrophages (M2 TAMs) in tumor microenvironment. Meanwhile, the tumor-infiltrating CD4+ and CD8+ T cells were increased. And the calreticulin and HMGB1 may be potential candidate proteins improving the immunosuppressive tumor microenvironment. Taken together, our project suggests that ferroptosis can promote anti-tumor immune response by reversing immunosuppressive microenvironment, indicating that ferroptosis inducer is a promising therapeutic strategy in HNSCC.

Experimental Study of lncRNA RP11-815M8.1 Promoting Osteogenic Differentiation of Human Bone Marrow Mesenchymal Stem Cells.

OBJECTIVE: This study is aimed at investigating the role of long noncoding RNA (lncRNA) RP11-815M8.1 in the osteogenic differentiation of human bone marrow mesenchymal stem cells (hBMSCs). METHODS: RT-PCR was used to detect the expression of lncRNA RP11-815M8.1 before and after osteogenic differentiation of hBMSCs. The lncRNA RP11-815M8.1 in hBMSCs was overexpressed or silenced via lentiviral transfection. The transfection efficiency was detected by RT-PCR, and the proliferation of hBMSCs was determined by CCK-8. After 14 days of osteogenic differentiation of transfected hBMSCs, the expression of osteogenic transcription factors (ALP, OCN, OPN, Runx2, and Osterix) was detected by alizarin red staining and RT-PCR. The mRNAs directly regulated by lncRNA RP11-815M8.1 and targeted miRNAs were analyzed according to the positional relationship between lncRNA and mRNA in the genome and miRanda software. RESULTS: The expression of lncRNA RP11-815M8.1 enhanced with increasing osteogenic differentiation time of hBMSCs. Two days after the transfection of hBMSCs, lncRNA RP11-815M8.1 expression was significantly increased in the overexpression group and significantly decreased in the knockdown group, compared to control cells. The CCK-8 assay showed that overexpression and knockdown of lncRNA RP11-815M8.1 did not affect the proliferation of hBMSCs. After 14 days of differentiation of hBMSCs, stronger alizarin red staining was observed in the overexpression groups, and the expression of osteogenic transcription factors was increased in the overexpression group compared to the control. In the knockdown group, alizarin red staining and the expression of osteogenic transcription factors were decreased. Bioinformatics analysis showed that lncRNA RP11-815M8.1 was directly associated with one mRNA, 27 interacting miRNAs, and 20 miRNA-targeted mRNAs. CONCLUSION: The osteogenic differentiation of hBMSCs can be promoted by lncRNA RP11-815M8.1 in vitro.

High-Accuracy Guide Star Catalogue Generation with a Machine Learning Classification Algorithm.

In order to detect gravitational waves and characterise their sources, three laser links were constructed with three identical satellites, such that interferometric measurements for scientific experiments can be carried out. The attitude of the spacecraft in the initial phase of laser link docking is provided by a star sensor (SSR) onboard the satellite. If the attitude measurement capacity of the SSR is improved, the efficiency of establishing laser linking can be elevated. An important technology for satellite attitude determination using SSRs is star identification. At present, a guide star catalogue (GSC) is the only basis for realising this. Hence, a method for improving the GSC, in terms of storage, completeness, and uniformity, is studied in this paper. First, the relationship between star numbers in the field of view (FOV) of a staring SSR, together with the noise equivalent angle (NEA) of the SSR-which determines the accuracy of the SSR-is discussed. Then, according to the relationship between the number of stars (NOS) in the FOV, the brightness of the stars, and the size of the FOV, two constraints are used to select stars in the SAO GSC. Finally, the performance of the GSCs generated by Decision Trees (DC), K-Nearest Neighbours (KNN), Support Vector Machine (SVM), the Magnitude Filter Method (MFM), Gradient Boosting (GB), a Neural Network (NN), Random Forest (RF), and Stochastic Gradient Descent (SGD) is assessed. The results show that the GSC generated by the KNN method is better than those of other methods, in terms of storage, uniformity, and completeness. The KNN-generated GSC is suitable for high-accuracy spacecraft applications, such as gravitational detection satellites.

Identification and characterization of a novel adiponectin receptor agonist adipo anti-inflammation agonist and its anti-inflammatory effects in vitro and in vivo.

BACKGROUND AND PURPOSE: Adiponectin (APN) is an adipokine secreted from adipocytes that binds to APN receptors AdipoR1 and AdipoR2 and exerts an anti-inflammatory response through mechanisms not fully understood. There is a need to develop small molecules that activate AdipoR1 and AdipoR2 and to be used to inhibit the inflammatory response in lipopolysaccharide (LPS)-induced endotoxemia and other inflammatory disorders. EXPERIMENTAL APPROACH: We designed 10 new structural analogues of an AdipoR agonist, AdipoRon (APR), and assessed their anti-inflammatory properties. Bone marrow-derived macrophages (BMMs) and peritoneal macrophages (PEMs) were isolated from mice. Levels of pro-inflammatory cytokines were measured by reverse transcription and real-time quantitative polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay (ELISA) and microarray in LPS-induced endotoxemia mice and diet-induced obesity (DIO) mice in which systemic inflammation prevails. Western blotting, immunohistochemistry (IHC), siRNA interference and immunoprecipitation were used to detect signalling pathways. KEY RESULTS: A novel APN receptor agonist named adipo anti-inflammation agonist (AdipoAI) strongly suppresses inflammation in DIO and endotoxemia mice, as well as in cultured macrophages. We also found that AdipoAI attenuated the association of AdipoR1 and APPL1 via myeloid differentiation marker 88 (MyD88) signalling, thus inhibiting activation of nuclear factor kappa B (NF-κB), mitogen-activated protein kinase (MAPK) and c-Maf pathways and limiting the production of pro-inflammatory cytokines in LPS-induced macrophages. CONCLUSION AND IMPLICATIONS: AdipoAI is a promising alternative therapeutic approach to APN and APR to suppress inflammation in LPS-induced endotoxemia and other inflammatory disorders via distinct signalling pathways.

Potential roles of miR-335-5p on pathogenesis of experimental periodontitis.

BACKGROUND AND OBJECTIVE: Periodontitis is a prevalent oral disease responsible for tooth loss. MicroRNAs have been proven crucial in bone disorders over the past decades. Promotive effect on osteogenic activities by microRNA-335-5p (miR-335-5p) has been well demonstrated, but its role involved in the pathogenesis of periodontitis remains elusive. In this study, we established experimental periodontitis (EP) on transgenic mice overexpressing miR-335-5p (335-Tg) to investigate the novel effects of miR-335-5p on periodontal inflammation and bone loss. METHODS: Experimental periodontitis was established via ligation. The expression of inflammatory and osteoclastic genes was examined by quantitative real-time PCR (qPCR). Morphology of alveolar bone was analyzed by microcomputed tomography (µCT). Hematoxylin and eosin (H&E), tartrate-resistant acid phosphatase (TRAP), and Toll-like receptor 4 (TLR4) immunohistochemistry (IHC) staining were conducted for histological analysis. RESULTS: The expression of miR-335-5p decreased significantly in the periodontal tissues of EP. Compared to the WT-EP group, µCT analysis showed less bone loss in the 335-Tg-EP group accompanying with a decreased number of TRAP-positive osteoclasts. H&E and IHC staining exhibited attenuated inflammation and TLR4 expression in the 335-Tg-EP group. Furthermore, reduced expressions of IL-1ß, IL-6, TNF-α, and TLR4 were also detected in the 335-Tg-EP group. Overexpression of miR-335-5p in vivo weakened the periodontal bone destruction and inflammation compared with the WT-EP group. CONCLUSIONS: Our data exhibit novel roles of miR-335-5p in preventing bone loss and inflammation in experimental periodontitis.

A novel Lipidoid-MicroRNA formulation promotes calvarial bone regeneration.

Specific microRNAs (miRs) and the Wnt signaling pathway play critical roles in regulating bone development and homeostasis. Our previous studies revealed the ability of miR-335-5p to promote osteogenic differentiation by downregulating Wnt antagonist Dickkopf-1 (DKK1). The purpose of this study was to use nano-materials to efficiently deliver miR-335-5p into osteogenic cells for tissue engineering applications. We synthesized and screened a library of 12 candidate nano-lipidoids，of which L8 was identified as the preferred biodegradable lipidoid for miRNA molecule delivery into cells. We then investigated whether a lipidoid-miRNA formulation of miR-335-5-p (LMF-335) could successfully deliver miR-335-5-p into cells to promote osteogenesis in vitro and calvarial bone healing in vivo. Transfection of C3H10T1/2 cells and bone marrow stromal cells (BMSCs) with LMF-335 led to decreased expression of DKK1 and increased expression of the key osteogenic genes. LMF-335 and LMF-335-transfected BMSCs were then used in combination with silk scaffolds to evaluate healing of critical-size calvarial bone defects in mice. The results revealed significant new bone formation in the defects in LMF-335 groups as compared with control groups. In conclusion, this first report supports the notion that lipidoid delivery of miRNA can be used to induce osteogenic differentiation of stem cells and bone regeneration.

Compensation of Horizontal Gravity Disturbances for High Precision Inertial Navigation.

Horizontal gravity disturbances are an important factor that affects the accuracy of inertial navigation systems in long-duration ship navigation. In this paper, from the perspective of the coordinate system and vector calculation, the effects of horizontal gravity disturbance on the initial alignment and navigation calculation are simultaneously analyzed. Horizontal gravity disturbances cause the navigation coordinate frame built in initial alignment to not be consistent with the navigation coordinate frame in which the navigation calculation is implemented. The mismatching of coordinate frame violates the vector calculation law, which will have an adverse effect on the precision of the inertial navigation system. To address this issue, two compensation methods suitable for two different navigation coordinate frames are proposed, one of the methods implements the compensation in velocity calculation, and the other does the compensation in attitude calculation. Finally, simulations and ship navigation experiments confirm the effectiveness of the proposed methods.

A Model of Gravity Vector Measurement Noise for Estimating Accelerometer Bias in Gravity Disturbance Compensation.

Compensation of gravity disturbance can improve the precision of inertial navigation, but the effect of compensation will decrease due to the accelerometer bias, and estimation of the accelerometer bias is a crucial issue in gravity disturbance compensation. This paper first investigates the effect of accelerometer bias on gravity disturbance compensation, and the situation in which the accelerometer bias should be estimated is established. The accelerometer bias is estimated from the gravity vector measurement, and a model of measurement noise in gravity vector measurement is built. Based on this model, accelerometer bias is separated from the gravity vector measurement error by the method of least squares. Horizontal gravity disturbances are calculated through EGM2008 spherical harmonic model to build the simulation scene, and the simulation results indicate that precise estimations of the accelerometer bias can be obtained with the proposed method.

Design and Calibration of a Novel Bio-Inspired Pixelated Polarized Light Compass.

Animals, such as Savannah sparrows and North American monarch butterflies, are able to obtain compass information from skylight polarization patterns to help them navigate effectively and robustly. Inspired by excellent navigation ability of animals, this paper proposes a novel image-based polarized light compass, which has the advantages of having a small size and being light weight. Firstly, the polarized light compass, which is composed of a Charge Coupled Device (CCD) camera, a pixelated polarizer array and a wide-angle lens, is introduced. Secondly, the measurement method of a skylight polarization pattern and the orientation method based on a single scattering Rayleigh model are presented. Thirdly, the error model of the sensor, mainly including the response error of CCD pixels and the installation error of the pixelated polarizer, is established. A calibration method based on iterative least squares estimation is proposed. In the outdoor environment, the skylight polarization pattern can be measured in real time by our sensor. The orientation accuracy of the sensor increases with the decrease of the solar elevation angle, and the standard deviation of orientation error is 0 . 15 ∘ at sunset. Results of outdoor experiments show that the proposed polarization navigation sensor can be used for outdoor autonomous navigation.

[A review on microRNAs regulation in osteoclast differentiation and function].

MicroRNAs (miRNAs) are small non-coding RNAs that contain 22 to 25 nucleotides and play important roles in post-transcriptional regulation of target genes. MiRNAs are involved in cell proliferation, differentiation, apoptosis, inflammation, and cancer development. Alveolar bone resorption is the main clinical manifestation of periodontitis. Osteoclasts are unique cells regulated by osteoblasts and inflammatory cytokines and are responsible for bone resorption in periodontitis. Recently, miRNAs have emerged as an important regulator of osteoclast differentiation and function. In this study, we review the recent research progress on the effects of miRNAs on osteoclast differentiation and function, particularly the mechanisms of miRNAs-mediated osteoclast formation and bone loss in periodontitis.

An evaluation of skylight polarization patterns for navigation.

Skylight polarization provides a significant navigation cue for certain polarization-sensitive animals. However, the precision of the angle of polarization (AOP) of skylight for vehicle orientation is not clear. An evaluation of AOP must be performed before it is utilized. This paper reports an evaluation of AOP of skylight by measuring the skylight polarization patterns of clear and cloudy skies using a full-sky imaging polarimetry system. AOP measurements of skylight are compared with the pattern calculated by the single-scattering Rayleigh model and these differences are quantified. The relationship between the degree of polarization (DOP) and the deviation of AOP of skylight is thoroughly studied. Based on these, a solar meridian extracted method is presented. The results of experiments reveal that the DOP is a key parameter to indicate the accuracy of AOP measurements, and all the output solar meridian orientations extracted by our method in both clear and cloudy skies can achieve a high accuracy for vehicle orientation.

Compass information extracted from a polarization sensor using a least-squares algorithm.

Skylight polarization provides a significant navigation cue for certain polarization-sensitive animals. We designed a polarization navigation sensor based on the polarization sensitivity mechanism of insects. In this paper, the principle of our polarization navigation sensor is introduced. The relationship between the degree of polarization (DOP) and the error of the angle of polarization (AOP) is examined. A new DOP and AOP calculation algorithm using a linear least-squares algorithm is presented. The results of simulation and experiments reveal the essentiality of DOP calculation and demonstrate the efficiency and accuracy of the proposed algorithm.

A novel angle computation and calibration algorithm of bio-inspired sky-light polarization navigation sensor.

Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot be used in a satellite denied environment. The remarkable navigation ability of animals shows that the pattern of the polarization sky can be used for navigation. A bio-inspired POLarization Navigation Sensor (POLNS) is constructed to detect the polarization of skylight. Contrary to the previous approach, we utilize all the outputs of POLNS to compute input polarization angle, based on Least Squares, which provides optimal angle estimation. In addition, a new sensor calibration algorithm is presented, in which the installation angle errors and sensor biases are taken into consideration. Derivation and implementation of our calibration algorithm are discussed in detail. To evaluate the performance of our algorithms, simulation and real data test are done to compare our algorithms with several exiting algorithms. Comparison results indicate that our algorithms are superior to the others and are more feasible and effective in practice.

Design of a device for sky light polarization measurements.

Sky polarization patterns can be used both as indicators of atmospheric turbidity and as a sun compass for navigation. The objective of this study is to improve the precision of sky light polarization measurements by optimal design of the device used. The central part of the system is composed of a Charge Coupled Device (CCD) camera; a fish-eye lens and a linear polarizer. Algorithms for estimating parameters of the polarized light based on three images are derived and the optimal alignments of the polarizer are analyzed. The least-squares estimation is introduced for sky light polarization pattern measurement. The polarization patterns of sky light are obtained using the designed system and they follow almost the same patterns of the single-scattering Rayleigh model. Deviations of polarization angles between observation and the theory are analyzed. The largest deviations occur near the sun and anti-sun directions. Ninety percent of the deviations are less than 5° and 40% percent of them are less than 1°. The deviations decrease evidently as the degree of polarization increases. It also shows that the polarization pattern of the cloudy sky is almost identical as in the blue sky.

Improved iterative calibration for triaxial accelerometers based on the optimal observation.

This paper presents an improved iterative nonlinear calibration method in the gravitational field for both low-grade and high-grade triaxial accelerometers. This calibration method assumes the probability density function of a Gaussian distribution for the raw outputs of triaxial accelerometers. A nonlinear criterion function is derived as the maximum likelihood estimation for the calibration parameters and inclination vectors, which is solved by the iterative estimation. First, the calibration parameters, including the scale factors, misalignments, biases and squared coefficients are estimated by the linear least squares method according to the multi-position raw outputs of triaxial accelerometers and the initial inclination vectors. Second, the sequence quadric program method is utilized to solve the nonlinear constrained optimization to update the inclination vectors according to the estimated calibration parameters and raw outputs of the triaxial accelerometers. The initial inclination vectors are supplied by normalizing raw outputs of triaxial accelerometers at different positions without any a priori knowledge. To overcome the imperfections of models, the optimal observation scheme is designed according to some maximum sensitivity principle. Simulation and experiments show good estimation accuracy for calibration parameters and inclination vectors.