Humoral Immunity Links Candida albicans Infection and Celiac Disease

Objective The protein Hwp1, expressed on the pathogenic phase of Candida albicans, presents sequence analogy with the gluten protein gliadin and is also a substrate for transglutaminase. This had led to the suggestion that C. albicans infection (CI) may be a triggering factor for Celiac disease (CeD) onset. We investigated cross-immune reactivity between CeD and CI. Methods Serum IgG levels against recombinant Hwp1 and serological markers of CeD were measured in 87 CeD patients, 41 CI patients, and 98 healthy controls (HC). IgA and IgG were also measured in 20 individuals from each of these groups using microchips sensitized with 38 peptides designed from the N-terminal of Hwp1. Results CI and CeD patients had higher levels of anti-Hwp1 (p= 0.0005 and p= 0.004) and anti-gliadin (p= 0.002 and p= 0.0009) antibodies than HC but there was no significant difference between CeD and CI patients. CeD and CI patients had higher levels of anti-transglutaminase IgA than HC (p= 0.0001 and p= 0.0039). During CI, the increase in anti-Hwp1 paralleled the increase in anti-gliadin antibodies. Microchip analysis showed that CeD patients were more reactive against some Hwp1 peptides than CI patients, and that some deamidated peptides were more reactive than their native analogs. Binding of IgG from CeD patients to Hwp1 peptides was inhibited by gamma III gliadin peptides. Conclusions Humoral cross-reactivity between Hwp1 and gliadin was observed during CeD and CI. Increased reactivity to Hwp1 deamidated peptide suggests that transglutaminase is involved in this interplay. These results support the hypothesis that CI may trigger CeD onset in genetically-susceptible individuals.

Comparative study of human age estimation based on hand-crafted and deep face features

In the past few years, human facial age estimation has drawn a lot of attention in the computer vision and pattern recognition communities because of its important applications in age-based image retrieval, security control and surveillance, biomet- rics, human-computer interaction (HCI) and social robotics. In connection with these investigations, estimating the age of a person from the numerical analysis of his/her face image is a relatively new topic. Also, in problems such as Image Classification the Deep Neural Networks have given the best results in some areas including age estimation. In this work we use three hand-crafted features as well as five deep features that can be obtained from pre-trained deep convolutional neural networks. We do a comparative study of the obtained age estimation results with these features.

GFAP Isoforms in Adult Mouse Brain with a Focus on Neurogenic Astrocytes and Reactive Astrogliosis in Mouse Models of Alzheimer Disease

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