Intrinsic Surface Effects of Tantalum and Titanium on Integrin α5β1/ ERK1/2 Pathway-Mediated Osteogenic Differentiation in Rat Bone Mesenchymal Stromal Cells

Background/Aims: Accumulating evidence demonstrates the superior osteoinductivity of tantalum (Ta) to that of titanium (Ti); however, the mechanisms underlying these differences are unclear. Thus, the objective of the present study was to examine the effects of Ta and Ti surfaces on osteogenesis using rat bone mesenchymal stromal cells (rBMSCs) as a model. Methods: Ta and Ti substrates were polished to a mirror finish to minimize the influences of structural factors, and the intrinsic surface effects of the two materials on the integrin α5β1/mitogen-activated protein kinases 3 and 1 (ERK1/2) cascade-mediated osteogenesis of rBMSCs were evaluated. Alkaline phosphatase (ALP) activity, Alizarin Red staining, real-time polymerase chain reaction, and western blot assays of critical osteogenic markers were conducted to evaluate the effects of the two substrates on cell osteogenesis. Moreover, the role of the integrin α5β1/ERK1/2 pathway on the osteoinductive performance of Ta and Ti was assessed by up- and down-regulation of integrin α5 and β1 with RNA interference, as well as through ERK1/2 inhibition with U0126. Results: Osteogenesis of rBMSCs seeded on the Ta surface was superior to that of cells seeded on the Ti surface in terms of ALP activity, extracellular matrix calcification, and the expression of integrin α5, integrin β1, ERK1/2, Runt-related transcription factor 2, osteocalcin, collagen type I, and ALP at both the mRNA and protein levels. Moreover, down-regulation of integrin α5 or integrin β1, or ERK1/2 inhibition severely impaired the osteoblastic differentiation on the Ta surface. By contrast, over-expression of integrin α5 or integrin β1 improved osteogenesis on the Ti substrates, while subsequent ERK1/2 inhibition abrogated this effect. Conclusion: The integrin α5β1/ERK1/2 pathway plays a crucial role in regulating rBMSCs osteogenic differentiation; thus, the greater ability of a Ta surface to trigger integrin α5β1/ERK1/2 signaling may explain its better osteoinductivity. The different effects of Ta and Ti surfaces on rBMSC osteogenesis are considered to be related to the conductive behaviors between integrin α5β1 and the oxides spontaneously formed on the two metals. These results should facilitate the development of engineering strategies with Ta and Ti surfaces for improved osteogenesis in endosteal implants

Comprehensive analyses of glycolysis-related lncRNAs for ovarian cancer patients

Abstract Background Not only glycolysis but also lncRNAs play a significant role in the growth, proliferation, invasion and metastasis of of ovarian cancer (OC). However, researches about glycolysis -related lncRNAs (GRLs) remain unclear in OC. Herein, we first constructed a GRL-based risk model for patients with OC. Methods The processed RNA sequencing (RNA-seq) profiles with clinicopathological data were downloaded from TCGA and glycolysis-related genes (GRGs) were obtained from MSigDB. Pearson correlation coefficient between glycolysis-related genes (GRGs) and annotated lncRNAs (|r| > 0.4 and p < 0.05) were calculated to identify GRLs. After screening prognostic GRLs, a risk model based on five GRLs was constructed using Univariate and Cox regression. The identified risk model was validated by two validation sets. Further, the differences in clinicopathology, biological function, hypoxia score, immune microenvironment, immune checkpoint, immune checkpoint blockade, chemotherapy drug sensitivity, N6-methyladenosine (m6A) regulators, and ferroptosis-related genes between risk groups were explored by abundant algorithms. Finally, we established networks based on co-expression, ceRNA, cis and trans interaction. Results A total of 535 GRLs were gained and 35 GRLs with significant prognostic value were identified. The prognostic signature containing five GRLs was constructed and validated and can predict prognosis. The nomogram proved the accuracy of the model for predicting prognosis. After computing hypoxia score of each sample by ssGSEA, we found patients with higher risk scores exhibited higher hypoxia score and high hypoxia score was a risk factor. It was revealed that a total of 21 microenvironment cells (such as Central memory CD4 T cell, Neutrophil, Regulatory T cell and so on) and Stromal score had significant differences between the two groups. Four immune checkpoint genes (CD274, LAG3, VTCN1, and CD47) showed disparate expression levels in the two groups. Besides, 16 m6A regulators and 126 ferroptosis-related genes were expressed higher in the low-risk group. GSEA revealed that the risk groups were associated with tumor-related pathways. The two risk groups were confirmed to be sensitive to several chemotherapeutic agents and patients in the low-risk group were more sensitive to ICB therapy. The networks based on co-expression, ceRNA, cis and trans interaction provided insights into the regulatory mechanisms of GRLs. Conclusions Our identified and validated risk model based on five GRLs is an independent prognostic factor for OC patients. Through comprehensive analyses, findings of our study uncovered potential biomarker and therapeutic target for the risk model based on the GRLs

Expectation propagation approach to joint channel estimation and decoding for OFDM systems

We propose a message-passing algorithm of joint channel estimation and decoding for OFDM systems, where expectation propagation is exploited to deal with channel estimation. Specially, the message updating is formulated into a recursive form. As a result, for system with K subcarriers and L channel taps, only O(K + L) messages need to be tracked, and meanwhile they can be efficiently calculated using FFT with complexity O(K|A| + K log2 K), where |A| denotes the constellation size. Numerical experiments show that our algorithm achieves BER performance within 0.5 dB of the knownchannel bound

Message-passing receiver for joint channel estimation and decoding in 3D massive MIMO-OFDM systems

In this paper, we address the design of message-passing receiver for massive multiple-input multiple-output orthogonal frequency division multiplex (MIMO-OFDM) systems. With the aid of the central limit argument and Taylor-series approximation, a computationally efficient receiver that performs joint channel estimation and decoding is devised by the framework of expectation propagation. In particular, the local belief defined at the channel transition function is expanded up to the second order with Wirtinger calculus, to transform the messages sent by the channel transition function to a tractable form. As a result, the channel impulse response between each pair of antennas is estimated by Gaussian message passing. In addition, a variational expectation-maximization-based method is derived to learn the channel power-delay profiles. The proposed scheme is assessed in 3D massive MIMO-OFDM systems with spatially correlated channels, and the empirical results corroborate its superiority in terms of performance and complexity

Low-complexity iterative detection for large-scale multiuser MIMO-OFDM systems using approximate message passing

One of the challenges in the design of large-scale multiuser MIMO-OFDM systems is developing low-complexity detection algorithms. To achieve this goal, we leverage message passing algorithms over the factor graph that represents the multiuser MIMO-OFDM systems and approximate the original discrete messages with continuous Gaussian messages through the use of the minimum Kullback-Leibler (KL) divergence criterion. Several signal processing techniques are then proposed to achieve near-optimal performance at low complexity. First, the principle of expectation propagation is employed to compute the approximate Gaussian messages, where the symbol belief is approximated by a Gaussian distribution and then the approximate message is calculated from the Gaussian approximate belief. In addition, the approximate symbol belief can be computed by the a posteriori probabilities fed back from channel decoders, which reduces the complexity dramatically. Second, the first-order approximation of the message is utilized to further simplify the message updating, leading to an algorithm that is equivalent to the AMP algorithm proposed by Donoho et al. Finally, the message updating is further simplified using the central-limit theorem. Compared with the single tree search sphere decoder (STS-SD) and the iterative (turbo) minimum mean-square error based soft interference cancellation (MMSE-SIC) in the literature through extensive simulations, the proposed message passing algorithms can achieve a near-optimal performance while the complexity is decreased by tens of times for a 64 64 MIMO system. In addition, it is shown that the proposed message passing algorithms exhibit desirable tradeoffs between performance and complexity for a low-dimensional MIMO system

Plasma Pharmacokinetics and Tissue Distribution of Doxorubicin in Rats following Treatment with Astragali Radix

Doxorubicin (DOX) is an essential component in chemotherapy, and Astragali Radix (AR) is a widely used tonic herbal medicine. The combination of DOX and AR offers widespread, well-documented advantages in treating cancer, e.g., reducing the risk of adverse effects. This study mainly aims to uncover the impact of AR on DOX disposition in vivo. Rats received a single intravenous dose of 5 mg/kg DOX following a single-dose co-treatment or multiple-dose pre-treatment of AR (10 g/kg × 1 or × 10). The concentrations of DOX in rat plasma and six tissues, including heart, liver, lung, kidney, spleen, and skeletal muscle, were determined by a fully validated LC-MS/MS method. A network-based approach was further employed to quantify the relationships between enzymes that metabolize and transport DOX and the targets of nine representative AR components in the human protein–protein interactome. We found that short-term (≤10 d) AR administration was ineffective in changing the plasma pharmacokinetics of DOX in terms of the area under the concentration–time curve (AUC, 1303.35 ± 271.74 μg/L*h versus 1208.74 ± 145.35 μg/L*h, p > 0.46), peak concentrations (Cmax, 1351.21 ± 364.86 μg/L versus 1411.01 ± 368.38 μg/L, p > 0.78), and half-life (t1/2, 31.79 ± 5.12 h versus 32.05 ± 6.95 h, p > 0.94), etc. Compared to the isotype control group, DOX concentrations in six tissues slightly decreased under AR pre-administration but only showed statistical significance (p < 0.05) in the liver. Using network analysis, we showed that five of the nine representative AR components were not localized to the vicinity of the DOX disposition-associated module. These findings suggest that AR may mitigate DOX-induced toxicity by affecting drug targets rather than drug disposition

Expectation propagation based iterative group wise detection for large-scale multiuser MIMO-OFDM systems

For the spatially correlated multiuser MIMOOFDM channels, the conventional iterative MMSE-SIC detection suffers from a considerable performance loss. In this paper, we use the factor graph framework to design robust detection algorithms by clustering a group of symbols to combat the spatial correlation and using the principle of expectation propagation to improve message passing. Furthermore, as the complexity of detection becomes one of the issues in the design of large-scale multiuser MIMO-OFDM systems, we propose a low-complexity approximate message-passing algorithm by opening the channel transition node, which eliminates the expensive matrix inversions involved in the MMSE-SIC based algorithms. Finally, numerical results are presented to verify the proposed algorithms