Activation of AIM2 by hepatitis B virus results in antiviral immunity that suppresses hepatitis C virus during coinfection.

IMPORTANCE: Clinical data suggest that Hepatitis C virus (HCV) levels are generally lower in Hepatitis B virus (HBV) co-infected patients, but the mechanism is unknown. Here, we show that HBV, but not HCV, activated absent in melanoma-2. This in turn results in inflammasome-mediated cleavage of pro-IL-18, leading to an innate immune activation cascade that results in increased interferon-γ, suppressing both viruses.

Development and validation of a tumor immune cell infiltration-related gene signature for recurrence prediction by weighted gene co-expression network analysis in prostate cancer.

Introduction: Prostate cancer (PCa) is the second most common malignancy in men. Despite multidisciplinary treatments, patients with PCa continue to experience poor prognoses and high rates of tumor recurrence. Recent studies have shown that tumor-infiltrating immune cells (TIICs) are associated with PCa tumorigenesis. Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to derive multi-omics data for prostate adenocarcinoma (PRAD) samples. The CIBERSORT algorithm was used to calculate the landscape of TIICs. Weighted gene co-expression network analysis (WGCNA) was performed to determine the candidate module most significantly associated with TIICs. LASSO Cox regression was applied to screen a minimal set of genes and construct a TIIC-related prognostic gene signature for PCa. Then, 78 PCa samples with CIBERSORT output p-values of less than 0.05 were selected for analysis. WGCNA identified 13 modules, and the MEblue module with the most significant enrichment result was selected. A total of 1143 candidate genes were cross-examined between the MEblue module and active dendritic cell-related genes. Results: According to LASSO Cox regression analysis, a risk model was constructed with six genes (STX4, UBE2S, EMC6, EMD, NUCB1 and GCAT), which exhibited strong correlations with clinicopathological variables, tumor microenvironment context, antitumor therapies, and tumor mutation burden (TMB) in TCGA-PRAD. Further validation showed that the UBE2S had the highest expression level among the six genes in five different PCa cell lines. Discussion: In conclusion, our risk-score model contributes to better predicting PCa patient prognosis and understanding the underlying mechanisms of immune responses and antitumor therapies in PCa.

Evaluating the Spatiotemporal Characteristics of Agricultural Eco-Efficiency Alongside China's Carbon Neutrality Targets.

Agriculture has the dual effect of contributing to both carbon emissions and sequestration, and thus plays a critical role in mitigating global climate change and achieving carbon neutrality. Agricultural eco-efficiency (AEE) is an important measurement through which we can assess the efforts toward reduced emissions and increased sequestration. The purpose of this study was to understand the relationship between China's target of carbon neutrality and AEE through an evaluative model, so as to improve AEE and ultimately achieve sustainable agricultural development. The Super-SBM model scientifically measures the AEE based on provincial panel data collected between 2000 and 2020. We selected kernel density function and spatial distribution to explore the spatial and temporal evolutionary trends, and used a Tobit model to identify the drivers of AEE. The research shows that (1) China's agricultural system functions as a net carbon sink, with all provinces' agricultural carbon sequestration levels recorded as higher than their carbon emissions from 2000 to 2020. (2) Despite sequestration levels, the level of AEE in China is not high enough, and the average efficiency level from 2000 to 2020 is 0.7726, showing an overall trend where AEE decreased at first and then increased. (3) The AEE of each province is clearly polarized; there are obvious core-periphery characteristics and spatial distribution of clustered contiguous areas. Central provinces generally have lower efficiency, eastern and northeastern provinces have higher efficiency, and northeastern provinces always remain in the high-efficiency group. (4) Influencing factors show that urbanization, upgrading of industrial structure, financial support for agriculture, and mechanization have a significant positive impact on AEE. These findings have important implications for the promotion of the low-carbon green development of Chinese agriculture.

A Systematic Calibration Modeling Method for Redundant INS with Multi-Sensors Non-Orthogonal Configuration.

Because of the non-orthogonal configuration of multi-sensors, the redundant inertial navigation system (INS) has a more complex error model compared with the traditional orthogonal INS, and the complexity of sensors configuration also increases the difficulty of error separation. Based on sufficient analysis of the error principle of redundant IMUs, a generalized high-accuracy calibration modeling method which is suitable for filtering method systematic calibration is summarized in this paper, and it has been applied to an RIMU prototype consisting of four ring laser gyros (RLGs) and four quartz accelerometers. Through the rotational excitation of the three-axis turntable in the laboratory, the high-precision filtering method systematic calibration of the RIMU is achieved, and static navigation and dynamic vehicle test experiments are also carried out. The experimental results reflect that the positioning accuracy can be obviously improved by using this new systematic calibration error model and the validity of this modeling method is also verified.

Precision Temperature Control for the Laser Gyro Inertial Navigation System in Long-Endurance Marine Navigation.

In the Ring Laser Gyro Inertial Navigation System (RLG INS), the temperature characteristics of the accelerometer can directly influence the measurement results. In order to improve navigation accuracy in long-endurance marine navigation, the operating temperature of the accelerometer should be precisely controlled. Based on thermal studies on the accelerometer, temperature control precision should be better than 0.01 °C to achieve 1 × 10-5 m/s2 output accuracy of the accelerometer. However, this conclusion is obtained by approximate calculations and cannot be directly applied to different inertial navigation systems. In order to verify this thermal conclusion and broaden its application, the Back Propagation Neural Network (BP-NN) algorithm is adopted to validate the feasibility of temperature control in this paper. In addition, a multi-level temperature control system is also set up and carefully designed to support the validation and experiments under different conditions. Test results of the temperature control system prove that operating temperature variation can be reduced to 0.01 °C. Meanwhile, the standard deviation per hundred seconds of the accelerometer outputs, after temperature control, reaches 1 × 10-5 m/s2. Static altitude and navigation results were improved by 41.97% and 62.91%, respectively, with the precision temperature control system, which meets the long-endurance marine navigation requirements.

Calibration of a three-dimensional laser Doppler velocimeter in a land integrated navigation system.

In the land navigation field, a laser Doppler velocimeter (LDV), which is able to measure the speed of a carrier, can be combined with a strapdown inertial navigation system (SINS) to form an integrated navigation system. To realize the integrated navigation positioning of a free motion carrier on the ground accurately, this paper introduces a split-reuse three-dimensional (3D) LDV. For the error parameters during application, a Kalman filtering calibration method with the assistance of a differential global positioning system (DGPS) is put forward in this paper. Two groups of integrated navigation experiments are designed to validate the effectiveness of this method and the universality of the obtained parameters. The experimental results show that the calibration method proposed in this paper is effective and the 3D LDV after compensation can greatly improve the positioning accuracy of the integrated navigation. The maximum horizontal position errors of the two experiments calculated by the dead reckoning of the 3D LDV and the gyroscopes are 4.2 m and 2.9 m, and the maximum altitude errors are 0.8 m and 0.9 m, respectively.

Two-dimensional laser Doppler velocimeter and its integrated navigation with a strapdown inertial navigation system.

In the field of land navigation, a laser Doppler velocimeter (LDV) can be used to provide the velocity of a vehicle for an integrated navigation system with a strapdown inertial navigation system. In order to suppress the influence of vehicle jolts on a one-dimensional (1D) LDV, this paper designs a split-reuse two-dimensional (2D) LDV. The velocimeter is made up of two 1D velocimeter probes that are mirror-mounted. By the different effects of the vertical vibration on the two probes, the velocimeter can calculate the forward velocity and the vertical velocity of a vehicle. The results of the vehicle-integrated navigation experiments show that the 2D LDV not only can actually suppress the influence of vehicle jolts and greatly improve the navigation positioning accuracy, but also can give high-precision altitude information. The maximum horizontal position errors of the two experiments are 2.6 m and 3.2 m in 1.9 h, and the maximum altitude errors are 0.24 m and 0.22 m, respectively.

Plasmonic Bi metal as cocatalyst and photocatalyst: The case of Bi/(BiO)2CO3 and Bi particles.

Semimetal bismuth with plasmonic properties has triggered increased interests. In this work, a facile strategy was developed to synthesize the Bi/(BiO)2CO3 (Bi-BOC) nanocomposites and Bi elemental photocatalysts. The Bi nanoparticles were produced via the insitu reduction of (BiO)2CO3 by NaBH4. The catalysts were utilized for the photocatalytic NO removal under visible light and UV illumination. Significantly, the photocatalytic capability of the Bi-BOC was highly enhanced with an unprecedented NO removal of 63.6%. The Bi metal demonstrated a direct plasmonic photocatalytic NO removal ratio of 53.6% under UV irradiation. The significantly enhanced photocatalytic capability of Bi-BOC can be ascribed to the synergistic effects of the SPR effect, enhanced visible-light-harvesting and the efficient electron-hole separation induced by Bi nanoparticles. The Bi nanoparticles can perform as a non-noble metal-based plasmonic cocatalyst for advancing photocatalytic ability. The mechanism of photocatalytic NO oxidation was proposed and compared under both visible light and UV illumination. Furthermore, the Bi-BOC photocatalysts showed good photochemical stability under repeated tests. This work could not only offer new insights into in-situ fine-tune reduction strategy for Bi-based photocatalysts, but also proves the potentials of utilizing low cost Bi cocatalysts as a substitute for noble metals to improve other photocatalysts.