Severe acute respiratory syndrome (SARS) is a life-threatening disease for which accurate diagnosis is essential. Although many tools have been developed for the diagnosis of SARS, false-positive reactions in negative sera may occur because of cross-reactivity with other coronaviruses. We have raised polyclonal and monoclonal antibodies (Abs) using a recombinant form of the SARS virus nucleocapsid protein. Cross-reactivity of these anti-SARS Abs against human coronavirus (HCoV) 229E and HCoV OC43 were determined by Western blotting. The Abs produced reacted with recombinant SARS virus nucleocapsid protein, but not with HCoV 229E or HCoV OC43.

Hepatic steatosis, a hepatic component of metabolic syndrome, is common and may progress to steatohepatitis and cirrhosis. The liver X receptor-α (LXRα)-sterol regulatory element binding protein-1c (SREBP-1c) pathway plays a key role in hepatic steatosis. This study investigated the potential of ajoene, a stable garlic by-product, to inhibit high fat diet (HFD)-induced hepatic steatosis and the underlying mechanism. Ajoene treatment attenuated fat accumulation and induction of lipogenic genes in the liver of HFD-fed mice. Blood biochemical analyses and histopathologic examinations showed that ajoene prevented liver injury with the inhibition of oxidative stress, as evidenced by thiobarbituric acid reactive substances formation and nitrotyrosinylation. Moreover, ajoene treatment inhibited LXRα agonist (T0901317)-mediated SREBP-1c activation, and transactivation of the lipogenic target genes in hepatocytes. Ajoene was found to activate AMP-activated protein kinase (AMPK) via LKB1, responsible for the inhibition of p70 ribosomal S6 kinase-1 (S6K1). The ability of ajoene to repress T0901317-induced SREBP-1c expression was antagonized by inhibition of AMPK or activation of S6K1, supporting the role of these kinases in the antisteatotic effect. Our results demonstrate that ajoene has an effect of activating AMPK through LKB1 and inhibit S6K1 activity, contributing to the prevention of SREBP-1c-mediated hepatic lipogenesis via the inhibition of LXRα activity.

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The induction of phase II enzymes and phase III transporters contributes to the metabolism, detoxification of xenobiotics, antioxidant capacity, redox homeostasis and cell viability. Transactivation of the genes that encode for phase II enzymes and phase III transporters is coordinatively regulated by activating transcription factors in response to external stimuli. Comprehensive studies indicate that antioxidant phytochemicals promote the induction of phase II enzymes and/or phase III transporters through various signaling pathways, including phosphoinositide 3-kinase, protein kinase C, and mitogen-activated protein kinases. This paper focuses on the molecular mechanisms and signaling pathways responsible for the transactivation of genes encoding for these proteins, as orchestrated by a series of transcription factors and related signaling components.

Retinal fundus images are used to detect organ damage from vascular diseases (e.g. diabetes mellitus and hypertension) and screen ocular diseases. We aimed to assess convolutional neural network (CNN) models that predict age and sex from retinal fundus images in normal participants and in participants with underlying systemic vascular-altered status. In addition, we also tried to investigate clues regarding differences between normal ageing and vascular pathologic changes using the CNN models. In this study, we developed CNN age and sex prediction models using 219,302 fundus images from normal participants without hypertension, diabetes mellitus (DM), and any smoking history. The trained models were assessed in four test-sets with 24,366 images from normal participants, 40,659 images from hypertension participants, 14,189 images from DM participants, and 113,510 images from smokers. The CNN model accurately predicted age in normal participants; the correlation between predicted age and chronologic age was R 2 = 0.92, and the mean absolute error (MAE) was 3.06 years. MAEs in test-sets with hypertension (3.46 years), DM (3.55 years), and smoking (2.65 years) were similar to that of normal participants; however, R 2 values were relatively low (hypertension, R 2 = 0.74; DM, R 2 = 0.75; smoking, R 2 = 0.86). In subgroups with participants over 60 years, the MAEs increased to above 4.0 years and the accuracies declined for all test-sets. Fundus-predicted sex demonstrated acceptable accuracy (area under curve > 0.96) in all test-sets. Retinal fundus images from participants with underlying vascular-altered conditions (hypertension, DM, or smoking) indicated similar MAEs and low coefficients of determination (R 2) between the predicted age and chronologic age, thus suggesting that the ageing process and pathologic vascular changes exhibit different features. Our models demonstrate the most improved performance yet and provided clues to the relationship and difference between ageing and pathologic changes from underlying systemic vascular conditions. In the process of fundus change, systemic vascular diseases are thought to have a different effect from ageing. Research in context. Evidence before this study. The human retina and optic disc continuously change with ageing, and they share physiologic or pathologic characteristics with brain and systemic vascular status. As retinal fundus images provide high-resolution in-vivo images of retinal vessels and parenchyma without any invasive procedure, it has been used to screen ocular diseases and has attracted significant attention as a predictive biomarker for cerebral and systemic vascular diseases. Recently, deep neural networks have revolutionised the field of medical image analysis including retinal fundus images and shown reliable results in predicting age, sex, and presence of cardiovascular diseases. Added value of this study. This is the first study demonstrating how a convolutional neural network (CNN) trained using retinal fundus images from normal participants meas...

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Objective This study aimed to evaluate the following null hypothesis there are no differences in the morphology of the temporomandibular joint (TMJ) structures in relation to vertical and sagittal cephalometric patterns. Methods This retrospective study was performed with 131 participants showing no TMJ symptoms. The participants were divided into Class I, II, and III groups on the basis of their sagittal cephalometric relationships and into hyperdivergent, normodivergent, and hypodivergent groups on the basis of their vertical cephalometric relationships. The following measurements were performed using cone-beam computed tomography images and compared among the groups condylar volume, condylar size (width, length, and height), fossa size (length and height), and condyle-to-fossa joint spaces at the anterior, superior, and posterior condylar poles. Results The null hypothesis was rejected. The Class III group showed larger values for condylar width, condylar height, and fossa height than the Class II group ( p < 0.05). Condylar volume and superior joint space in the hyperdivergent group were significantly smaller than those in the other two vertical groups ( p < 0.001), whereas fossa length and height were significantly larger in the hyperdivergent group than in the other groups ( p < 0.01). The hypodivergent group showed a greater condylar width than the hyperdivergent group ( p < 0.01). The sagittal and vertical cephalometric patterns showed statistically significant interactions for fossa length and height. Conclusions TMJ morphology differed across diverse skeletal cephalometric patterns. The fossa length and height were affected by the interactions of the vertical and sagittal skeletal patterns.