Non-alcoholic steatohepatitis (NASH) is considered the advanced stage of non-alcoholic fatty liver disease (NAFLD). It is characterized by liver steatosis, inflammation and different degrees of fibrosis.Although the exact mechanisms by which fatty liver progresses to NASH are still not well understood, innate and adaptive immune responses seem to be essential key regulators in the establishment, progression, and chronicity of these disease. Diet-induced lipid overload of parenchymal and non-parenchymal liver cells is considered the first step for the development of fatty liver with the consequent organelle dysfunction, cellular stress and liver injury. These will generate the production of pro-inflammatory cytokines, chemokines and damage-associated molecular patterns (DAMPs) that will upregulate the activation of Kupffer cells (KCs) and monocyte-derived macrophages (MMs) favoring the polarization of the tolerogenic environment of the liver to an immunogenic phenotype with the resulting transdifferentiation of hepatic stellate cells (HSCs) into myofibroblasts developing fibrosis. In the long run, dendritic cells (DCs) will activate CD4+ T cells polarizing into the pro-inflammatory lymphocytes Th1 and Th17 worsening the liver damage and inflammation. Therefore, the objective of this review is to discuss in a systematic way the mechanisms known so far of the immune and non-proper immune liver cells in the development and progression of NASH.
Currently, alcoholic liver disease (ALD) is one of the most prevalent chronic liver diseases worldwide, representing one of the main etiologies of cirrhosis and hepatocellular carcinoma (HCC). Although we do not know the exact mechanisms by which only a selected group of patients with ALD progress to the final stage of HCC, the role of the gut microbiota within the progression to HCC has been intensively studied in recent years. To date, we know that alcohol-induced gut dysbiosis is an important feature of ALD with important repercussions on the severity of this disease. In essence, an increased metabolism of ethanol in the gut induced by an excessive alcohol consumption promotes gut dysfunction and bacterial overgrowth, setting a leaky gut. This causes the translocation of bacteria, endotoxins, and ethanol metabolites across the enterohepatic circulation reaching the liver, where the recognition of the pathogen-associated molecular patterns via specific Toll-like receptors of liver cells will induce the activation of the nuclear factor kappa-B pathway, which releases pro-inflammatory cytokines and chemokines. In addition, the mitogenic activity of hepatocytes will be promoted and cellular apoptosis will be inhibited, resulting in the development of HCC. In this context, it is not surprising that microbiota-regulating drugs have proven effectiveness in prolonging the overall survival of patients with HCC, making attractive the implementation of these drugs as co-adjuvant for HCC treatment.
Computer vision and artificial intelligence applications in medicine are becoming increasingly important day by day, especially in the field of image technology. In this paper we cover different artificial intelligence advances that tackle some of the most important worldwide medical problems such as cardiology, cancer, dermatology, neurodegenerative disorders, respiratory problems, and gastroenterology. We show how both areas have resulted in a large variety of methods that range from enhancement, detection, segmentation and characterizations of anatomical structures and lesions to complete systems that automatically identify and classify several diseases in order to aid clinical diagnosis and treatment. Different imaging modalities such as computer tomography, magnetic resonance, radiography, ultrasound, dermoscopy and microscopy offer multiple opportunities to build automatic systems that help medical diagnosis, taking advantage of their own physical nature. However, these imaging modalities also impose important limitations to the design of automatic image analysis systems for diagnosis aid due to their inherent characteristics such as signal to noise ratio, contrast and resolutions in time, space and wavelength. Finally, we discuss future trends and challenges that computer vision and artificial intelligence must face in the coming years in order to build systems that are able to solve more complex problems that assist medical diagnosis.
Nonalcoholic fatty liver disease (NAFLD) is a serious Background: worldwide health problem, with an estimated global prevalence of 24%
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