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To explore the effect of Rho kinase inhibitor on intestinal injury in septic rats and its possible mechanism.Thirty-two male Sprague-Dawley (SD) rats were randomly divided into sham operation group (Sham group), Rho kinase inhibitor Y-27632 control group (Y+Sham group), sepsis model group [cecal ligation and puncture (CLP) group] and Y-27632 pretreatment group (Y+CLP group), with 8 rats in each group. Rat sepsis model was reproduced by CLP. The rats in the Sham group and Y+Sham group were only separated and moved the cecum without ligation and perforation. The rats in the Y+Sham group and Y+CLP group were pretreated with intraperitoneal injection of Y-27632 solution 5 mg/kg 15 minutes before operation; the rats in the Sham group and CLP group were intraperitoneally injected with the same amount of phosphate buffered saline (PBS). Twenty-four hours after operation, the heart blood was collected and the serum diamine oxidase (DAO) content was determined by enzyme-linked immunosorbent assay (ELISA). Then the small intestine tissue was collected, the pathological changes of the intestinal tissue were observed under the light microscope after hematoxylin-eosin (HE) staining, and Chiu's score was performed. The positive expressions of Rho-related coiled-coil kinase 1 (ROCK1) and nuclear factor-κB (NF-κB) in intestinal tissue were detected by immunohistochemistry. ELISA was used to detect the levels of tumor necrosis factor-α (TNF-α) and interleukin-10 (IL-10) in intestinal tissue homogenate.The intestinal tissue structure of the Sham group and Y+Sham group was intact and the mucosa was arranged neatly. Compared with the Sham group, the intestinal mucosa of the CLP group was arranged disorderly, with a large number of inflammatory cells infiltration, and the Chiu's score was significantly increased (3.83±0.27 vs. 0.12±0.11, P0.05), indicating that those rats suffered from septic intestinal injury. Compared with the CLP group, the degree of necrosis of intestinal epithelial cells in the Y+CLP group was reduced, a small amount of inflammatory cells infiltration was seen, and the Chiu's score was significantly decreased (2.85±0.21 vs. 3.83±0.27, P0.05), indicating that Y-27632 pretreatment could alleviate intestinal injury in septic rats. Compared with the Sham group, the positive expressions of intestinal tissue ROCK1 and NF-κB, the contents of serum DAO and intestinal homogenate TNF-α in the CLP group were significantly increased [ROCK1 expression (A value): 0.19 (0.18, 0.22) vs. 0.10 (0.09, 0.11), NF-κB expression (A value): 0.40±0.02 vs. 0.15±0.01, DAO (ng/L): 287.81±23.31 vs. 144.92±17.72, TNF-α (ng/L): 101.08±5.62 vs. 74.81±5.56, all P0.05], the level of intestinal homogenate IL-10 was significantly decreased (μg/L: 55.16±5.20 vs. 95.95±7.53, P0.05). Compared with the CLP group, the positive expressions of intestinal tissue ROCK1, NF-κB, the contents of serum DAO and intestinal homogenate TNF-α in the Y+CLP group were significantly decreased [ROCK1 expression (A value): 0.15 (0.13, 0.18) vs. 0.19 (0.18, 0.22), NF-κB expression (A value): 0.28±0.01 vs. 0.40±0.02, DAO (ng/L): 243.34±19.76 vs. 287.81±23.31, TNF-α (ng/L): 90.41±8.79 vs. 101.08±5.62, all P0.05], while the level of intestinal homogenate IL-10 was significantly increased (μg/L: 66.15±5.74 vs. 55.16±5.20, P0.05), indicating that the protective effect of Y-27632 pretreatment on sepsis intestinal injury rats might be related to the regulation of RhoA/ROCK1/NF-κB signaling pathway.Rho kinase inhibitors can reduce intestinal injury in septic rats, and the mechanism may be related to inhibiting RhoA/ROCK1/NF-κB signaling pathway and reducing intestinal inflammation in septic rats.

Image quality assessment (IQA) has become a hot issue in image processing, which aims to evaluate the quality of images automatically by a metric being consistent with subjective evaluations. Though deep learning based techniques have been applied to IQA models to achieve much progress, conventional IQA models that adopt deliberately designed features are still meaningful because by which we can learn what features are quality-aware and hence understand more about the way we improve image quality by enhancing quality-aware features. The first stage of conventional IQA model design is the quality-aware feature selection. Phase congruency (PC), as one of efficient saliency maps, which takes advantages of early visual feature, operates in frequency domain to measure local structure such as edges, corners, lines, etc. by computing the local amplitude and local energy in multiple scales. Conventional local PC feature is calculated with log-Gabor based filtration in several orientations, and is usually combined with other features in quality estimating. Recently, researchers suggested that spatially circular symmetric filters, such as gradient magnitude (GM) and Laplacian of Gaussian (LoG), are highly-efficient quality features that have been widely used in various IQA model designs. By considering the first-order derivative property of GM and the second-order derivative property of LoG, the two features are a suitable pairs for PC compositions while keeping the circular symmetric characteristic. Therefore, we use GM and LoG to construct a novel PC feature map and only use this feature map to build a full-reference (FR) IQA model, which is proved to be state-of-the-art on three benchmark databases. Furthermore, we replace the PC algorithm in the state-of-the-art FSIM metric with our PC computation, which achieves improved performance. This study suggests that the proposed circular symmetric PC feature is a high efficient quality feature and can be exclusively used in IQA model designs.

Image quality assessment aims at estimating the subject quality of images and builds models to high efficiently evaluate the perceptual quality of the image for many applications. Because the human visual system (HVS) is highly sensitive to structural information, various image features have been studied and widely applied in IQA metrics design. Previous work has validated that the image gradient magnitude and the Laplacian of Gaussian (LOG) operator are efficient structural features in IQA tasks. Most of the IQA metrics work capably only when the distorted image is totally registered with the reference image, and perform poorly on images even with small translations. In this paper, we suggested an FR-IQA method with a simple combination of the gradient magnitude and the LOG signals, which obtains satisfied performance in evaluating image quality while considering the shift-invariance property for not well-registered reference and distortion image pair. Experimental results show that the proposed model works robustly on three large scale subjective IQA databases which contain a variety of distortion types and levels, stays in the state-of-the-art FR-IQA models and achieves the best performance in terms of weighted average score over the three databases. Furthermore, we proved that the proposed model performs better in translation-invariance test compared with the competitors.

In the previous work, the LoG (Laplacian of Gaussian) signal that is the earliest stage output of human visual neural system was suggested to be useful in image quality assessment (IQA) model design. This work considered that LoG signal carried crucial structural information of IQA in the position of its zero-crossing and proposed a Non-shift Edge (NSE) based IQA model. In this study, we focus on another aspect of the properties of the LoG signal, i.e., LoG whitens the power spectrum of natural images. Here our interest is that: when exposed to unnatural images, specifically distorted images, how does the HVS whitening this type of signals? In this paper, we first investigate the whitening filter for natural image and distorted image respectively, and then suggest that the LoG is also a whitening filter for distorted images to some extent. Based on this fact, we deploy the LOG signal in the task of IQA model design by applying two very simple distance metrics, i.e., the MSE (mean square error) and the correlation. The proposed models are analyzed according to the evaluation performance on three subjective databases. The experimental results validate the usability of the LoG signal in IQA model design and that the proposed models stay in the state-of-the-art IQA models.