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Melanoma skin cancer is one of the most dangerous forms of skin cancer because it grows fast and causes most of the skin cancer deaths. Hence, early detection is a very important task to treat melanoma. In this article, we propose a skin lesion segmentation method for dermoscopic images based on the U-Net architecture with VGG-16 encoder and the semantic segmentation. Base on the segmented skin lesion, diagnostic imaging systems can evaluate skin lesion features to classify them. The proposed method requires fewer resources for training, and it is suitable for computing systems without powerful GPUs, but the training accuracy is still high enough (above 95 %). In the experiments, we train the model on the ISIC dataset – a common dermoscopic image dataset. To assess the performance of the proposed skin lesion segmentation method, we evaluate the Sorensen-Dice and the Jaccard scores and compare to other deep learning-based skin lesion segmentation methods. Experimental results showed that skin lesion segmentation quality of the proposed method are better than ones of the compared methods.

BACKGROUND: In clinical medicine, low-dose radiographic image noise reduces the quality of the detected image features and may have a negative impact on disease diagnosis. OBJECTIVE: In this study, Adaptive Projection Network (APNet) is proposed to reduce noise from low-dose medical images. METHODS: APNet is developed based on an architecture of the U-shaped network to capture multi-scale data and achieve end-to-end image denoising. To adaptively calibrate important features during information transmission, a residual block of the dual attention method throughout the encoding and decoding phases is integrated. A non-local attention module to separate the noise and texture of the image details by using image adaptive projection during the feature fusion. RESULTS: To verify the effectiveness of APNet, experiments on lung CT images with synthetic noise are performed, and the results demonstrate that the proposed approach outperforms recent methods in both quantitative index and visual quality. In addition, the denoising experiment on the dental CT image is also carried out and it verifies that the network has a certain generalization. CONCLUSIONS: The proposed APNet is an effective method that can reduce image noise and preserve the required image details in low-dose radiographic images. [ABSTRACT FROM AUTHOR]

Cytokine imbalance and cellular migration to inflammatory sites are critical components of allergic diseases. Redirecting cytokine imbalance and inhibiting cell migration therefore represent important therapeutic strategies for the treatment of these disorders. To study the in vitro effect of ebastine, a novel non-sedating H1 receptor antagonist, on cytokine secretion and migration of activated T cells, as well as production of pro-inflammatory cytokines by macrophages. Peripheral T cells obtained from healthy volunteers were cultured in wells coated with the combination of anti-CD3 monoclonal antibody (mAb) and anti-CD26 mAb, anti-CD3 mAb and anti-CD28 mAb, or anti-CD3 mAb with PMA, in the presence or absence of ebastine. T cell proliferation and the production of cytokines were measured by [3H]thymidine incorporation assay and ELISA, respectively. In addition, transendothelial migration of T cells and production of pro-inflammatory cytokines by macrophages were examined. Ebastine inhibited T cell proliferation and the production of IL-4, IL-5, IL-6, and TNF-α by T cells under each co-stimulatory condition tested, whereas it exhibited no effect on the production of IL-2 or IFN-γ. In addition, T cell migration and the production of such pro-inflammatory cytokines as TNF-α and IL-6 by macrophages were inhibited by ebastine. These results indicate that ebastine has a specific inhibitory effect on Th2-type cytokine production. Moreover, ebastine inhibited T cell migration and pro-inflammatory cytokine production by T cells and macrophages, suggesting that ebastine might be useful for the treatment of T cell-mediated allergic inflammatory disorders, including asthma, atopic dermatitis, and Th2-type autoimmune diseases. [ABSTRACT FROM AUTHOR]

CD26/dipeptidyl peptidase IV (DPPIV) is a cell surface-bound ectopeptidase with important roles in T-cell activation and tumour biology. We now report that CD26/DPPIV enhances sensitivity to apoptosis induced by the antineoplastic agents doxorubicin and etoposide. In particular, CD26/DPPIV presence is associated with increased susceptibility to the mitochondrial pathway of apoptosis, documented by enhanced cleavage of poly (ADP ribose) polymerase (PARP), caspase-3 and caspase-9, Bcl-xl, and Apaf-1, as well as increased expression of death receptor 5 (DR5). We also show that the caspase-9-specific inhibitor z-LEHD-fmk inhibits drug-mediated apoptosis, leading to decreased PARP and caspase-3 cleavage, and reduced DR5 expression. Importantly, through detailed studies that demonstrate the association between topoisomerase II alpha expression and DPPIV activity, our data provide further evidence of the key role played by CD26 in biological processes. [ABSTRACT FROM AUTHOR]