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Inflammatory bowel disease (IBD) is a group of intestinal inflammatory diseases characterized by chronic, recurrent, remitting, or progressive inflammation, which causes the disturbance of the homeostasis between immune cells, such as macrophages, epithelial cells, and microorganisms. Intestinal macrophages (IMs) are the largest population of macrophages in the body, and the abnormal function of IMs is an important cause of IBD. Most IMs come from the replenishment of blood monocytes, while a small part come from embryos and can self-renew. Stimulated by the intestinal inflammatory microenvironment, monocyte-derived IMs can interact with intestinal epithelial cells, intestinal fibroblasts, and intestinal flora, resulting in the increased differentiation of proinflammatory phenotypes and the decreased differentiation of anti-inflammatory phenotypes, releasing a large number of proinflammatory factors and aggravating intestinal inflammation. Based on this mechanism, inhibiting the secretion of IMs' proinflammatory factors and enhancing the differentiation of anti-inflammatory phenotypes can help alleviate intestinal inflammation and promote tissue repair. At present, the clinical medication of IBD mainly includes 5-aminosalicylic acids (5-ASAs), glucocorticoid, immunosuppressants, and TNF-α inhibitors. The general principle of treatment is to control acute attacks, alleviate the condition, reduce recurrence, and prevent complications. Most classical IBD therapies affecting IMs function in a variety of ways, such as inhibiting the inflammatory signaling pathways and inducing IM2-type macrophage differentiation. This review explores the current understanding of the involvement of IMs in the pathogenesis of IBD and their prospects as therapeutic targets. [ABSTRACT FROM AUTHOR]

Classification algorithms integrated with convolutional neural networks (CNN) display high accuracies in synthetic aperture radar (SAR) image classification. However, their consideration of spatial information is not comprehensive and effective, which causes poor performance in edges and complex regions. This paper proposes a Markov random field (MRF)-based algorithm for SAR image classification which fully considers the spatial constraints between superpixel regions. Firstly, the initialization of region labels is obtained by the CNN. Secondly, a probability field is constructed to improve the distribution of spatial relationships between adjacent superpixels. Thirdly, a novel region-level MRF is employed to classify the superpixels, which combines the intensity field and probability field in one framework. In our algorithm, the generation of superpixels reduces the misclassification at the pixel level, and region-level misclassification is rectified by the improvement of spatial description. Experimental results on simulated and real SAR images confirm the efficacy of the proposed algorithm for classification. [ABSTRACT FROM AUTHOR]

During the development of urban underground space in Chengdu, China, it was found that glauberite rocks in the Guankou formation of the Cretaceous system had extensive dissolution and exerted a serious impact on the safety of the project. At present, research on the transport and mechanical properties of glauberite under hydrostatic conditions in this area is limited. In this paper, the effects of hydrostatic dissolution and seepage on the transport and mechanical properties of glauberite are studied. The results show that the concentration of aqueous solution increases step by step with the increase in the dissolution time of glauberite in still water, indicating that the forward movement of the dissolution front of glauberite rock is not a continuous process and has intermittent characteristics. The dissolution and infiltration of mirabilite seriously deteriorates the physical structure of mirabilite, resulting in a decrease in elastic modulus and an increase in axial deformation, and a decrease in mechanical properties. There are a dissolution layer, dissolution front and undissolved area in the karst infiltration of calcium and mirabilite in the hydrostatic solution, so the mechanism of the calcium and mirabilite karst dissolution process is determined. Because of the dissolution characteristics of mirabilite, underground space development should prevent the uneven settlement of mirabilite, ground collapse, pit and chamber water gushing, corrosive groundwater and other geological problems. [ABSTRACT FROM AUTHOR]

The locations and breathing signal of people in disaster areas are significant information for search and rescue missions in prioritizing operations to save more lives. For detecting the living people who are lying on the ground and covered with dust, debris or ashes, a motion magnification-based method has recently been proposed. This current method estimates the locations and breathing signal of people from a drone video by assuming that only human breathing-related motions exist in the video. However, in natural disasters, background motions, such as swing trees and grass caused by wind, are mixed with human breathing, that distort this assumption, resulting in misleading or even no life signs locations. Therefore, the life signs in disaster areas are challenging to be detected due to the undesired background motions. Note that human breathing is a natural physiological phenomenon, and it is a periodic motion with a steady peak frequency; while background motion always involves complex space-time behaviors, their peak frequencies seem to be variable over time. Therefore, in this work we analyze and focus on the frequency properties of motions to model a frequency variability feature used for extracting only human breathing, while eliminating irrelevant background motions in the video, which would ease the challenge in detection and localization of life signs. The proposed method was validated with both drone and camera videos recorded in the wild. The average precision measures of our method for drone and camera videos were 0.94 and 0.92, which are higher than that of compared methods, demonstrating that our method is more robust and accurate to background motions. The implications and limitations regarding the frequency variability feature were discussed. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is characterized by the massive infiltration of various chronic inflammatory cells in synovia. In synovial fluid of patients with RA, M1 macrophages are dominant among all subtypes of macrophages, the mechanisms of macrophages polarization imbalance in RA has not been fully illuminated. The prostaglandin E2 (PGE2) augments M2 polarization in part via the cyclic adenosine monophosphate (cAMP)-cyclic AMP responsive element binding (CREB) signaling. However, previous study found constant stimulus of PGE2 on fibroblast-like synovial cells of adjuvant arthritis rats induced the decrease of cAMP, which is primarily caused by G protein-coupled receptor kinase 2 (GRK2)-induced EP4 over- desensitization. Whether GRK2 mediated-EP4 over-desensitization reduces the level of cAMP and inhibits M2 polarization in RA is unclear. Here we observed M1 macrophages were dominant in peritoneal macrophages (PMs), bone-marrow-derived macrophages (BMMs) and synovial macrophages of collagen-induced arthritis (CIA) mice. PGE2 stimulated M2 polarization via the EP4-cAMP-CREB in normal mice, while failed to promote M2 polarization in the PMs of CIA mice. Further, we found the EP4 over-desensitization stimulated by PGE2 induced abnormal PGE2-cAMP-CREB signaling as well as the imbalance of macrophage polarization. Targeted disruption of GRK2 in Raw264.7 (RAW) through GRK2 siRNA or CRISPR/Cas9 downregulated the M1 macrophage markers, upregulated the M2 macrophage markers and the EP4 membrane localization. The reduced M1/M2 ratio and increased p-CREB expression were observed in BMMs and PMs of GRK2+/− mice. This study highlighted a novel role of GRK2 in regulating macrophages function in RA and provided new idea for precision treatment of RA. [ABSTRACT FROM AUTHOR]

Video magnification reveals important and informative subtle variations in the world. These signals are often combined with large motions which result in significant blurring artifacts and haloes when conventional video magnification approaches are used. To counter these issues, this paper presents an amplitude-based filtering algorithm that can magnify small changes in video in presence of large motions. We seek to understand the amplitude characteristic of small changes and large motions with the goal of extracting accurate signals for visualization. Based on spectrum amplitude filtering, the large motions can be removed while small changes can still be magnified by Eulerian approach. An advantage of this algorithm is that it can handle large motions, whether they are linear or nonlinear. Our experimental results show that the proposed method can amplify subtle variations in the presence of large motion, as well as significantly reduce artifacts. We demonstrate the presented algorithm by comparing to the state-of-the-art and provide subjective and objective evidence for the proposed method. [ABSTRACT FROM AUTHOR]

Traditional constant false alarm rate (CFAR) detectors only use the contrast information between ship targets and clutter, and they suffer probability of detection (PD) degradation in multiple target situations. This paper proposes a correlation-based joint CFAR detector using adaptively-truncated statistics (hereafter called TS-2DLNCFAR) in SAR images. The proposed joint CFAR detector exploits the gray intensity correlation characteristics by building a two-dimensional (2D) joint log-normal model as the joint distribution (JPDF) of the clutter, so joint CFAR detection is realized. Inspired by the CFAR detection methodology, we design an adaptive threshold-based clutter truncation method to eliminate the high-intensity outliers, such as interfering ship targets, side-lobes, and ghosts in the background window, whereas the real clutter samples are preserved to the largest degree. A 2D joint log-normal model is accurately built using the adaptively-truncated clutter through simple parameter estimation, so the joint CFAR detection performance is greatly improved. Compared with traditional CFAR detectors, the proposed TS-2DLNCFAR detector achieves a high PD and a low false alarm rate (FAR) in multiple target situations. The superiority of the proposed TS-2DLNCFAR detector is validated on the multi-look Envisat-ASAR and TerraSAR-X data.

Hydrogen sulfide (H2S) is a colorless, flammable, extremely hazardous gas with a "rotten egg" smell. The human body produces small amounts of H2S and uses it as a signaling molecule. The cocktail method was used to evaluate the influence of H2S on the activities of CYP450 in rats, which were reflected by the changes of pharmacokinetic parameters of five specific probe drugs: bupropion, metroprolol, midazolam, omeprazole and tolbutamide, respectively. The rats were randomly divided into two groups, control group and H2S group. The H2S group rats were given 5 mg/kg NaHS by oral administration once a day for seven days. The mixture of five probes was given to rats through oral administration and the blood samples were obtained at a series of time-points through the caudal vein. The concentrations of probe drugs in rat plasma were measured by LC-MS. In comparing the H2S group with the control group, there was a statistically pharmacokinetics difference for midazolam and tolbutamide; the area under the plasma concentration-time curve (AUC) was decreased for midazolam (p < 0.05) and increased for tolbutamide (p < 0.05); while there was no statistical pharmacokinetics difference for bupropion, metroprolol and omeprazole. H2S could not influence the activities of CYP2B6, CYP2D6 and CYP2C19 in rats, while H2S could induce the activity of CYP3A4 and inhibit the activity of CYP2C9 in rats.