Exosomes derived from vMIP-II-Lamp2b gene-modified M2 cells provide neuroprotection by targeting the injured spinal cord, inhibiting chemokine signals and modulating microglia/macrophage polarization in mice.

Inflammation is one of the key injury factors for spinal cord injury (SCI). Exosomes (Exos) derived from M2 macrophages have been shown to inhibit inflammation and be beneficial in SCI animal models. However, lacking targetability restricts their application prospects. Considering that chemokine receptors increase dramatically after SCI, viral macrophage inflammatory protein II (vMIP-II) is a broad-spectrum chemokine receptor binding peptide, and lysosomal associated membrane protein 2b (Lamp2b) is the key membrane component of Exos, we speculated that vMIP-II-Lamp2b gene-modified M2 macrophage-derived Exos (vMIP-II-Lamp2b-M2-Exo) not only have anti-inflammatory properties, but also can target the injured area by vMIP-II. In this study, using a murine contusive SCI model, we revealed that vMIP-II-Lamp2b-M2-Exo could target the chemokine receptors which highly expressed in the injured spinal cords, inhibit some key chemokine receptor signaling pathways (such as MAPK and Akt), further inhibit proinflammatory factors (such as IL-1ß, IL-6, IL-17, IL-18, TNF-α, and iNOS), and promote anti-inflammatory factors (such as IL-4 and Arg1) productions, and the transformation of microglia/macrophages from M1 into M2. Moreover, the improved histological and functional recoveries were also found. Collectively, our results suggest that vMIP-II-Lamp2b-M2-Exo may provide neuroprotection by targeting the injured spinal cord, inhibiting some chemokine signals, reducing proinflammatory factor production and modulating microglia/macrophage polarization.

The beneficial effect of α-lipoic acid on spinal cord injury repair in rats is mediated through inhibition of oxidative stress: A transcriptomic analysis.

BACKGROUND: Oxidative stress is a crucial factor contributing to the occurrence and development of secondary damage in spinal cord injuries (SCI), ultimately impacting the recovery process. α-lipoic acid (ALA) exhibits potent antioxidant properties, effectively reducing secondary damage and providing neuroprotective benefits. However, the precise mechanism by which ALA plays its antioxidant role remains unknown. METHODS: We established a model of moderate spinal cord contusion in rats. Experimental rats were randomly divided into 3 distinct groups: the sham group, the model control group (SCI_Veh), and the ALA treatment group (SCI_ALA). The sham group rats were exposed only to the SC without contusion injury. Rats belonging to SCI_Veh group were not administered any treatment after SCI. Rats of SCI_ALA group were intraperitoneally injected with the corresponding volume of ALA according to body weight for three consecutive days after the surgery. Subsequently, three days after SCI, spinal cord samples were obtained from three groups of rats: the sham group, model control group, and administration group. Thereafter, total RNA was extracted from the samples and the expression of three sets of differential genes was analyzed by transcriptome sequencing technology. Real-time PCR was used to verify the sequencing results. The impact of ALA on oxidative stress in rats following SCI was assessed by measuring their total antioxidant capacity and hydrogen peroxide (H2O2) content. The effects of ALA on rat recovery following SCI was investigated through Beattie and Bresnahan (BBB) score and footprint analysis. RESULTS: The findings from the transcriptome sequencing analysis revealed that the model control group had 2975 genes with altered expression levels when compared to the ALA treatment group. Among these genes, 1583 were found to be upregulated while 1392 were down-regulated. Gene ontology (GO) displayed significant enrichment in terms of functionality, specifically in oxidative phosphorylation, oxidoreductase activity, and signaling receptor activity. The Kyoto encyclopedia of genes and genomes (KEGG) pathway was enriched in oxidative phosphorylation, glutathione metabolism and cell cycle. ALA was found to have multiple benefits for rats after SCI, including increasing their antioxidant capacity and reducing H2O2 levels. Additionally, it was effective in improving motor function (such as 7 days after SCI, the BBB score for SCI_ALA was 8.400 ± 0.937 compared to 7.050 ± 1.141 for SCI_Veh) and promoting histological recovery after SCI (The results of HE demonstrated that the percentage of damage area in was 44.002 ± 6.680 in the SCI_ALA and 57.215 ± 3.964 in the SCI_Veh at the center of injury.). The sequence data from this study has been deposited into Sequence Read Archive (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE242507). CONCLUSION: Overall, the findings of this study confirmed the beneficial effects of ALA on recovery in SCI rats through transcriptome sequencing, behavioral, as well histology analyses.

The polarization of microglia and infiltrated macrophages in the injured mice spinal cords: a dynamic analysis.

Background: Following spinal cord injury (SCI), a large number of peripheral monocytes infiltrate into the lesion area and differentiate into macrophages (Mø). These monocyte-derived Mø are very difficult to distinguish from the local activated microglia (MG). Therefore, the term Mø/MG are often used to define the infiltrated Mø and/or activated MG. It has been recognized that pro-inflammatory M1-type Mø/MG play "bad" roles in the SCI pathology. Our recent research showed that local M1 cells are mainly CD45-/lowCD68+CD11b+ in the subacute stage of SCI. Thus, we speculated that the M1 cells in injured spinal cords mainly derived from MG rather than infiltrating Mø. So far, their dynamics following SCI are not yet entirely clear. Methods: Female C57BL/6 mice were used to establish SCI model, using an Infinite Horizon impactor with a 1.3 mm diameter rod and a 50 Kdynes force. Sham-operated (sham) mice only underwent laminectomy without contusion. Flow cytometry and immunohistofluorescence were combined to analyze the dynamic changes of polarized Mø and MG in the acute (1 day), subacute (3, 7 and 14 days) and chronic (21 and 28 days) phases of SCI. Results: The total Mø/MG gradually increased and peaked at 7 days post-injury (dpi), and maintained at high levels 14, 21 and 28 dpi. Most of the Mø/MG were activated, and the Mø increased significantly at 1 and 3 dpi. However, with the pathological process, activated MG increased nearly to 90% at 7, 14, 21 and 28 dpi. Both M1 and M2 Mø were increased significantly at 1 and 3 dpi. However, they decreased to very low levels from 7 to 28 dpi. On the contrary, the M2-type MG decreased significantly following SCI and maintained at a low level during the pathological process.

Forecasting groundwater level of karst aquifer in a large mining area using partial mutual information and NARX hybrid model.

Predicting the groundwater level of karst aquifers in North China Coalfield is essential for early warning of mine water hazards and regional water resources management. However, the dynamic changes of strata structure and hydrogeological parameters driven by coal mining activity cause challenges to the process-oriented groundwater model. In order to achieve accurate prediction of groundwater level in large mining areas, this study was the first to use the data-driven Nonlinear Autoregressive with External Input (NARX) model to predict the groundwater level of six karst aquifer observation wells in Pingshuo Mining Area. Three variable input scenarios were set up, solely considering meteorological factors, anthropogenic disturbance factors, and considering both meteorological and anthropogenic disturbance factors. The novel partial mutual information (PMI) screening algorithm was adopted to determine optimized input variables in each scenario. The input and feedback delay coefficients of NARX model were determined by using Seasonal-trend Decomposition Procedure Based on Loess (STL) algorithm and auto- and cross-correlation functions. The results showed that PMI algorithm can effectively screen out the optimal input variables for predicting groundwater level, the NSE coefficients of the PMI-NARX models under the three scenarios were 38.81%, 4.26% and 41.46% higher than those of the corresponding control experiments, respectively. In addition, the prediction performance of the PMI-NARX built on the basis of meteorological factors is poor (NSE <0.63). However, in scenarios which solely use anthropogenic disturbance factors and both use meteorological and anthropogenic disturbance factors, the PMI-NARX coupling models exhibit good prediction performance (NSE and R2 are all greater than 0.8). Especially under solely considering anthropogenic disturbance factors scenario, the model still exhibited good prediction accuracy with a negligible number of input variables. The results can provide technical and theoretical support for the prediction of groundwater level in other mining areas.

Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique.

With the development of satellite load technology and very large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. A key goal of the on-board SAR imaging system design is to achieve high real-time processing performance under severe size, weight, and power consumption constraints. This paper presents a multi-node prototype system for real-time SAR imaging processing. We decompose the commonly used chirp scaling (CS) SAR imaging algorithm into two parts according to the computing features. The linearization and logic-memory optimum allocation methods are adopted to realize the nonlinear part in a reconfigurable structure, and the two-part bandwidth balance method is used to realize the linear part. Thus, float-point SAR imaging processing can be integrated into a single Field Programmable Gate Array (FPGA) chip instead of relying on distributed technologies. A single-processing node requires 10.6 s and consumes 17 W to focus on 25-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384. The design methodology of the multi-FPGA parallel accelerating system under the real-time principle is introduced. As a proof of concept, a prototype with four processing nodes and one master node is implemented using a Xilinx xc6vlx315t FPGA. The weight and volume of one single machine are 10 kg and 32 cm × 24 cm × 20 cm, respectively, and the power consumption is under 100 W. The real-time performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging.

A Novel Ship Detection Method Based on Gradient and Integral Feature for Single-Polarization Synthetic Aperture Radar Imagery.

With the rapid development of remote sensing technologies, SAR satellites like China's Gaofen-3 satellite have more imaging modes and higher resolution. With the availability of high-resolution SAR images, automatic ship target detection has become an important topic in maritime research. In this paper, a novel ship detection method based on gradient and integral features is proposed. This method is mainly composed of three steps. First, in the preprocessing step, a filter is employed to smooth the clutters and the smoothing effect can be adaptive adjusted according to the statistics information of the sub-window. Thus, it can retain details while achieving noise suppression. Second, in the candidate area extraction, a sea-land segmentation method based on gradient enhancement is presented. The integral image method is employed to accelerate computation. Finally, in the ship target identification step, a feature extraction strategy based on Haar-like gradient information and a Radon transform is proposed. This strategy decreases the number of templates found in traditional Haar-like methods. Experiments were performed using Gaofen-3 single-polarization SAR images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency. In addition, this method has the potential for on-board processing.

An Improved Adaptive Received Beamforming for Nested Frequency Offset and Nested Array FDA-MIMO Radar.

For the conventional FDA-MIMO (frequency diversity array multiple-input-multiple-output) Radar with uniform frequency offset and uniform linear array, the DOFs (degrees of freedom) of the adaptive beamformer are limited by the number of elements. A better performance-for example, a better suppression for strong interferences and a more desirable trade-off between the main lobe and side lobe-can be achieved with a greater number of DOFs. In order to obtain larger DOFs, this paper researches the signal model of the FDA-MIMO Radar with nested frequency offset and nested array, then proposes an improved adaptive beamforming method that uses the augmented matrix instead of the covariance matrix to calculate the optimum weight vectors and can be used to improve the output performances of FDA-MIMO Radar with the same element number or reduce the element number while maintain the approximate output performances such as the received beampattern, the main lobe width, side lobe depths and the output SINR (signal-to-interference-noise ratio). The effectiveness of the proposed scheme is verified by simulations.

A Decision Mixture Model-Based Method for Inshore Ship Detection Using High-Resolution Remote Sensing Images.

With the rapid development of optical remote sensing satellites, ship detection and identification based on large-scale remote sensing images has become a significant maritime research topic. Compared with traditional ocean-going vessel detection, inshore ship detection has received increasing attention in harbor dynamic surveillance and maritime management. However, because the harbor environment is complex, gray information and texture features between docked ships and their connected dock regions are indistinguishable, most of the popular detection methods are limited by their calculation efficiency and detection accuracy. In this paper, a novel hierarchical method that combines an efficient candidate scanning strategy and an accurate candidate identification mixture model is presented for inshore ship detection in complex harbor areas. First, in the candidate region extraction phase, an omnidirectional intersected two-dimension scanning (OITDS) strategy is designed to rapidly extract candidate regions from the land-water segmented images. In the candidate region identification phase, a decision mixture model (DMM) is proposed to identify real ships from candidate objects. Specifically, to improve the robustness regarding the diversity of ships, a deformable part model (DPM) was employed to train a key part sub-model and a whole ship sub-model. Furthermore, to improve the identification accuracy, a surrounding correlation context sub-model is built. Finally, to increase the accuracy of candidate region identification, these three sub-models are integrated into the proposed DMM. Experiments were performed on numerous large-scale harbor remote sensing images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency.

[Microanalysis study on lignin distribution of wood with different growth stress level by SEM-EDXA].

By virtue of FE-SEM and EDXA marked by Br element, the relationship between the lignin distribution and growth stress was micro-analyzed by normal wood of plantation Eucalyptus urophylla X E. grandis with different growth stress levels. The results indicated that the lignin contents of different cell wall layers were not related to the growth stress level, and the lignin content (from high level to low level) in sequence was cell corner, compound middle lamellae, S1, S2 and S3; The lignin contents in micro-morphological regions of wood fiber cell wall were decreased with the increase in growth stress and lignification process was delayed.