Two major isoforms of theHere, Runx2-II expression was found to be specifically stimulated by BMP-2 treatment or by Dlx5 overexpression. In addition, BMP-2, Dlx5, and Runx2-II were found to be expressed in osteogenic fronts and parietal bones of the developing cranial vault and Runx2-I and Msx2 in the sutural mesenchyme. Furthermore, Runx2 P1 promoter activity was strongly stimulated by Dlx5 overexpression, whereas Runx2 P2 promoter activity was not. Runx2 P1 promoter deletion analysis indicated that the Dlx5-specific response is due to sequences between ؊756 and ؊342 bp of the P1 promoter, where three Dlx5-response elements are located. Dlx5 responsiveness to these elements was confirmed by gel mobility shift assay and site-directed mutagenesis. Moreover, Msx2 specifically suppressed the Runx2 P1 promoter, and the responsible region overlaps with that recognized by Dlx5. In summary, Dlx5 specifically transactivates the Runx2 P1 promoter, and its action on the P1 promoter is antagonized by Msx2.The Runt-related transcription factor Runx2 plays an essential role in osteoblast differentiation and bone mineralization (1, 2). Two major isoforms are expressed from the mouse Runx2 locus, and these isoforms are generated by different promoter usage. Runx2 type I (Runx2-I), 2 referred to as the Cbfa1/p56 isoform or PEBP2␣A, is a 513-amino acid protein that starts with the amino acid sequence MRIPV (3) and is derived from the proximal P2 promoter of the gene (4). More recently, upstream exons of the Runx2 gene that potentially encode the N termini of Runx2 isoforms expressed in osteoblasts have been identified (5, 6). These upstream exons contain a 5Ј-untranslated region and encode the N-terminal 19 amino acids of Runx2 type II (Runx2-II; also referred to as Cbfa1/p57 and OSF2), which starts with the sequence MASNSL (7). This isoform is expressed from the P1 or "bone-related" upstream promoter (8), and its expression is predominant in osteoblasts (9). The alternative promoter usage strongly implies that the expression pattern of each isoform differs temporally and/or spatially. Indeed, they exhibit distinct expression patterns during bone development (10, 11). Thus, it is natural to assume that these two promoters differently respond to different extracellular signals or their downstream transcription factors because these promoters have distinct transcription factor-binding sites.Runx2 plays a central role in the BMP-2-induced trans-differentiation of C2C12 cells at an early restriction point by diverting them from the myogenic pathway to the osteogenic pathway (12, 13). We found that the homeobox gene Dlx5 is an upstream target of BMP-2 signaling and that it plays a pivotal role in stimulating the downstream osteogenic master transcription factor Runx2. In turn, Runx2 acts simultaneously or sequentially to induce the expression of bone-specific genes that represent BMP-2-induced osteogenic trans-differentiation. In addition, it has also been suggested that Dlx5 is a critical target of the inhibitory action of transform...
The most significant barrier to success in human activity recognition is extracting and selecting the right features. In traditional methods, the features are chosen by humans, which requires the user to have expert knowledge or to do a large amount of empirical study. Newly developed deep learning technology can automatically extract and select features. Among the various deep learning methods, convolutional neural networks (CNNs) have the advantages of local dependency and scale invariance and are suitable for temporal data such as accelerometer (ACC) signals. In this paper, we propose an efficient human activity recognition method, namely Iss2Image (Inertial sensor signal to Image), a novel encoding technique for transforming an inertial sensor signal into an image with minimum distortion and a CNN model for image-based activity classification. Iss2Image converts real number values from the X, Y, and Z axes into three color channels to precisely infer correlations among successive sensor signal values in three different dimensions. We experimentally evaluated our method using several well-known datasets and our own dataset collected from a smartphone and smartwatch. The proposed method shows higher accuracy than other state-of-the-art approaches on the tested datasets.
Recently, social media have been used by researchers to detect depressive symptoms in individuals using linguistic data from users’ posts. In this study, we propose a framework to identify social information as a significant predictor of depression. Using the proposed framework, we develop an application called the Socially Mediated Patient Portal (SMPP), which detects depression-related markers in Facebook users by applying a data-driven approach with machine learning classification techniques. We examined a data set of 4350 users who were evaluated for depression using the Center for Epidemiological Studies Depression (CES-D) scale. From this analysis, we identified a set of features that can distinguish between individuals with and without depression. Finally, we identified the dominant features that adequately assess individuals with and without depression on social media. The model trained on these features will be helpful to physicians in diagnosing mental diseases and psychiatrists in analysing patient behaviour.
Alcoholic liver disease (ALD) is a major liver disease worldwide and can range from simple steatosis or inflammation to fibrosis/cirrhosis, possibly through leaky gut and systemic endotoxemia. Many patients with alcoholic steatohepatitis (ASH) die within 60 days after clinical diagnosis due to the lack of an approved drug, and thus, synthetic and/or dietary agents to prevent ASH and premature deaths are urgently needed. We recently reported that a pharmacologically high dose of pomegranate extract prevented binge alcohol-induced gut leakiness and hepatic inflammation by suppressing oxidative and nitrative stress. Herein, we investigate whether a dietary antioxidant ellagic acid (EA) contained in many fruits, including pomegranate and vegetables, can protect against binge alcohol-induced leaky gut, endotoxemia, and liver inflammation. Pretreatment with a physiologically-relevant dose of EA for 14 days significantly reduced the binge alcohol-induced gut barrier dysfunction, endotoxemia, and inflammatory liver injury in mice by inhibiting gut dysbiosis and the elevated oxidative stress and apoptosis marker proteins. Pretreatment with EA significantly prevented the decreased amounts of gut tight junction/adherent junction proteins and the elevated gut leakiness in alcohol-exposed mice. Taken together, our results suggest that EA could be used as a dietary supplement for alcoholic hepatitis patients.
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