This paper attempts to provide a comprehensive review and characterize the problem of the semantic gap that is the key problem of content-based image retrieval and the current attempts in high-level semantic-based image retrieval being made to bridge it. Major recent publications are included in this review covering different aspects of the research in the area of high-level semantic features. In this paper the different methods of image retrieval systems are described and major categories of the state-of-the-art techniques in narrowing down the "semantic gap" are presented. Finally, based on existing technologies and the demand from real-world applications, a few promising future research directions are suggested.

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Hepatic ischemia reperfusion injury (R/I) is a hepatic pathophysiologic process occurs post liver transplantation surgery. It also comprises complex systemic process affecting multiple tissues and organs. Hepatic I/R has serious impact on liver function, even producing irreversible failure, which may trigger multiple organ dysfunction. Many factors, including anaerobic metabolism, mitochondrial damage, oxidative stress and secretion of reactive oxygen species (ROS), intracellular calcium overload, cytokines and chemokines produced by Kupffer cells (KCs) and neutrophils are involved in the pathogenesis of hepatic I/R processes. There are many treatment options to combat hepatic I/R injury but none has shown clear beneficial clinical evidence. The purpose of this review is to provide insights into the mechanisms of hepatic I/R injury, indicating the potential factors/signaling pathways involved in this event and available therapeutic approaches that may help to improve controlling hepatic I/R during liver surgery.

Ulcerative colitis is a chronic and incurable form of inflammatory bowel disease that can increase the risk of colitis-associated cancer and mortality. Limited treatment options are available for this condition, and the existing ones often come with non-tolerable adverse effects. This study is the first to examine the potential benefits of consuming (R,R)-BD-AcAc2, a type of ketone ester (KE), and intermittent fasting in treating chronic colitis induced by dextran sodium sulfate (DSS) in rats. We selected both protocols to enhance the levels of β-hydroxybutyrate, mimicking a state of nutritional ketosis and early ketosis, respectively. Our findings revealed that only the former protocol, consuming the KE, improved disease activity and the macroscopic and microscopic features of the colon while reducing inflammation scores. Additionally, the KE counteracted the DSS-induced decrease in the percentage of weight change, reduced the colonic weight-to-length ratio, and increased the survival rate of DSS-insulted rats. KE also showed potential antioxidant activities and improved the gut microbiome composition. Moreover, consuming KE increased the levels of tight junction proteins that protect against leaky gut and exhibited anti-inflammatory properties by reducing proinflammatory cytokine production. These effects were attributed to inhibiting NFκB and NLRP3 inflammasome activation and restraining pyroptosis and apoptosis while enhancing autophagy as revealed by reduced p62 and increased BECN1. Furthermore, the KE may have a positive impact on maintaining a healthy microbiome. To conclude, the potential clinical implications of our findings are promising, as (R,R)-BD-AcAc2 has a greater safety profile and can be easily translated to human subjects.

The goal of object level annotation is to locate and identify instances of an object category within an image. Nowadays, Most of the current object level annotation systems annotate the object according to the visual appearance in the image. Recognizing an object in an image based visual appearance yield ambiguity in object detection due to appearance confusion for example "sky" object may be annotated as "water" according to similarity in visual appearance. As a result, these systems don't recognize the objects in an image accurately due to the lack of scene context. In the task of visual object recognition, scene context can play important role in resolving the ambiguities in object detection. In order to solve the ambiguity problem, this paper presents a new technique for a context based object level annotation that considers both the semantic context and spatial context analysis to reduce ambiguous in object annotation.