N-myc downstream regulated gene 1 modulates Wnt-β-catenin signalling and pleiotropically suppresses metastasis

Wnt signalling has pivotal roles in tumour progression and metastasis; however, the exact molecular mechanism of Wnt signalling in the metastatic process is as yet poorly defined. Here we demonstrate that the tumour metastasis suppressor gene, NDRG1, interacts with the Wnt receptor, LRP6, followed by blocking of the Wnt signalling, and therefore, orchestrates a cellular network that impairs the metastatic progression of tumour cells. Importantly, restoring NDRG1 expression by a small molecule compound significantly suppressed the capability of otherwise highly metastatic tumour cells to thrive in circulation and distant organs in animal models. In addition, our analysis of clinical cohorts data indicate that Wnt+/NDRG−/LRP+ signature has a strong predictable value for recurrence-free survival of cancer patients. Collectively, we have identified NDRG1 as a novel negative master regulator of Wnt signalling during the metastatic progression, which opens an opportunity to define a potential therapeutic target for metastatic disease

Bone morphogenetic protein 7 in dormancy and metastasis of prostate cancer stem-like cells in bone

BMP7 released by bone marrow stromal cells induces reversible senescence of prostate cancer stem-like cells, and BMPR2 expression inversely correlates with bone metastasis and recurrence in prostate cancer patients

Judging Emotion from EEGs Based on an Association Mechanism

AbstractAuthors focus on the emotion of which common sense and attempt to compose a method that judge the user's emotion, based on EEGs. Emotion is judged from EEG features by an Association Mechanism. The Association Mechanism consists of the Concept Base and the Degree of Association. The methods of a Concept Base and a Degree of Association were proposed in the field of the natural language processing. In this paper, the research results are applied to EEGs. As a result, accuracy of emotion judgment from EEGs using the Association Mechanism was 57.6%. As a comparison, accuracy of emotion judgment at random was 25.0%, and accuracy of emotion judgment using SVM was 43.6%