16 research outputs found

    Dermal Pericytes Exhibit Declined Ability to Promote Human Skin Regeneration with Ageing in 3D Organotypic Culture Models.

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    The well documented decline in the regenerative ability of ageing human skin has been attributed to many factors including genomic instability, telomere shortening, poor nutrient sensing, cellular senescence, and stem cell exhaustion. However, a role for the dermal cellular and molecular microenvironment in skin ageing is just emerging. We previously showed that dermal pericytes co-operate with fibroblasts to improve human skin regeneration in an organotypic skin culture model, and even do so in the absence of fibroblasts. Here, we report that the number of dermal cells, particularly pericytes, declines significantly in human skin of donors aged > 50 years. Notably, aged pericytes promoted epidermal regeneration of neonatal keratinocytes in organotypic cultures and the resulting epithelium exhibited a Ki67+/ΔNp63+ basal layer and terminal differentiation. However, the epithelium lacked several features of homeostasis displaying lower levels of ΔNp63 expression, decreased LAMA5 deposition at the dermo-epidermal junction, and the absence of basement membrane and hemi-desmosome assembly. We conclude that a decline in pericyte incidence and function contribute to an impaired epidermal microenvironment and poor skin regeneration with ageing in the human skin

    KCNQ potassium channels modulate Wnt activity in gastro-oesophageal adenocarcinomas

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    Voltage-sensitive potassium channels play an important role in controlling membrane potential and ionic homeostasis in the gut and have been implicated in gastrointestinal (GI) cancers. Through large-scale analysis of 897 patients with gastro-oesophageal adenocarcinomas (GOAs) coupled with in vitro models, we find KCNQ family genes are mutated in ∼30% of patients, and play therapeutically targetable roles in GOA cancer growth. KCNQ1 and KCNQ3 mediate the WNT pathway and MYC to increase proliferation through resultant effects on cadherin junctions. This also highlights novel roles of KCNQ3 in non-excitable tissues. We also discover that activity of KCNQ3 sensitises cancer cells to existing potassium channel inhibitors and that inhibition of KCNQ activity reduces proliferation of GOA cancer cells. These findings reveal a novel and exploitable role of potassium channels in the advancement of human cancer, and highlight that supplemental treatments for GOAs may exist through KCNQ inhibitors

    Pericytes as microenvironmental regulators of skin tissue regeneration and skin ageing

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    © 2016 Dr. Lizhe ZhuangThis study focuses on how pericytes can contribute to the epidermal cell microenvironment in human skin, using a 3D organotypic co-culture model, I have shown that in the presence of pericytes, epidermal cells regenerate an epithelium that more closely resemble normal healthy skin with respect to basal cell morphology and various biochemical characteristics. Characterization of pericytes in skin ageing and their functionality in organotypic co-culture model suggests a microenvironmental modulatory role of pericytes in skin ageing and epithelial tissue repair

    Multimodal and Multi-Model Deep Fusion for Fine Classification of Regional Complex Landscape Areas Using ZiYuan-3 Imagery

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    Land cover classification (LCC) of complex landscapes is attractive to the remote sensing community but poses great challenges. In complex open pit mining and agricultural development landscapes (CMALs), the landscape-specific characteristics limit the accuracy of LCC. The combination of traditional feature engineering and machine learning algorithms (MLAs) is not sufficient for LCC in CMALs. Deep belief network (DBN) methods achieved success in some remote sensing applications because of their excellent unsupervised learning ability in feature extraction. The usability of DBN has not been investigated in terms of LCC of complex landscapes and integrating multimodal inputs. A novel multimodal and multi-model deep fusion strategy based on DBN was developed and tested for fine LCC (FLCC) of CMALs in a 109.4 km2 area of Wuhan City, China. First, low-level and multimodal spectral–spatial and topographic features derived from ZiYuan-3 imagery were extracted and fused. The features were then input into a DBN for deep feature learning. The developed features were fed to random forest and support vector machine (SVM) algorithms for classification. Experiments were conducted that compared the deep features with the softmax function and low-level features with MLAs. Five groups of training, validation, and test sets were performed with some spatial auto-correlations. A spatially independent test set and generalized McNemar tests were also employed to assess the accuracy. The fused model of DBN-SVM achieved overall accuracies (OAs) of 94.74% ± 0.35% and 81.14% in FLCC and LCC, respectively, which significantly outperformed almost all other models. From this model, only three of the twenty land covers achieved OAs below 90%. In general, the developed model can contribute to FLCC and LCC in CMALs, and more deep learning algorithm-based models should be investigated in future for the application of FLCC and LCC in complex landscapes

    SMAD4 and KCNQ3 alterations are associated with lymph node metastases in oesophageal adenocarcinoma

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    Metastasis in oesophageal adenocarcinoma (OAC) is an important predictor of survival. Radiological staging is used to stage metastases in patients, and guide treatment selection, but is limited by the accuracy of the approach. Improvements in staging will lead to improved clinical decision making and patient outcomes. Sequencing studies on primary tumours and pre-cancerous tissue have revealed the mutational landscape of OAC, and increasingly cheap and widespread sequencing approaches offer the potential to improve staging assessment. In this work we present an analysis of lymph node metastases found by radiological and pathological sampling, identifying new roles of the genes SMAD4 and KCNQ3 in metastasis. Through transcriptomic analysis we find that both genes are associated with canonical Wnt pathway activity, but KCNQ3 is uniquely associated with changes in planar cell polaritiy associated with non-canonical Wnt signalling. We go on to validate our observations in KCNQ3 in cell line and xenograph systems, showing that overexpression of KCNQ3 reduces wound closure and the number of metastases observed. Our results suggest both genes as novel biomarkers of metastatic risk and offer new potential routes to drug targeting
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