Identification of signaling pathways in early mammary gland development by mouse genetics

The mammary gland develops as an appendage of the ectoderm. The prenatal stage of mammary development is hormone independent and is regulated by sequential and reciprocal signaling between the epithelium and the mesenchyme. A number of recent studies using human and mouse genetics, in particular targeted gene deletion and transgenic expression, have identified some of the signals that control specific steps in development. This process involves cell specification and proliferation, reciprocal tissue interactions and cell migration. Since some of these events are recapitulated during tumorigenesis, an understanding of these signaling pathways may contribute to the development of targeted therapies and novel drugs

p63 regulates multiple signalling pathways required for ectodermal organogenesis and differentiation

Heterozygous germline mutations in p63, a transcription factor of the p53 family, result in abnormal morphogenesis of the skin and its associated structures, including hair follicles and teeth. In mice lacking p63, all ectodermal organs fail to develop, and stratification of the epidermis is absent. We show that the ectodermal placodes that mark early tooth and hair follicle morphogenesis do not form in p63-deficient embryos, although the multilayered dental lamina that precedes tooth placode formation develops normally. The N-terminally truncated isoform of p63 (?Np63) was expressed at high levels in embryonic ectoderm at all stages of tooth and hair development, and it was already dominant over the transactivating TAp63 isoform prior to epidermal stratification. Bmp7, Fgfr2b, Jag1 and Notch1 transcripts were co-expressed with ANp63 in wild-type embryos, but were not detectable in the ectoderm of p63 mutants. In addition, ?-catenin and Edar transcripts were significantly reduced in skin ectoderm. We also demonstrate that BMP2, BMP7 and FGF10 are potent inducers of p63 in cultured tissue explants. Hence, we suggest that p63 regulates the morphogenesis of surface ectoderm and its derivatives via multiple signalling pathways

Hierarchical clustering of a Finnish newspaper article collection with graded relevance assessments

Abstract Search facilitated with agglomerative hierarchical clustering methods was studied in a collection of Finnish newspaper articles (N = 53,893). To allow quick experiments, clustering was applied to a sample (N = 5,000) that was reduced with principal components analysis. The dendrograms were heuristically cut to find an optimal partition, whose clusters were compared with each of the 30 queries to retrieve the best-matching cluster. The fourlevel relevance assessment was collapsed into a binary one by (A) considering all the relevant and (B) only the highly relevant documents relevant, respectively. Single linkage (SL) was the worst method. It created many tiny clusters, and, consequently, searches enabled with it had high precision and low recall. The complete linkage (CL), average linkage (AL), and Ward's methods (WM) returned reasonably-sized clusters typically of 18-32 documents. Their recall (A: 27-52%, B: 50-82%) and precision (A: 83-90%, B: 18-21%) was higher than and comparable to those of the SL clusters, respectively. The AL and WM clustering had 1-8% better effectiveness than nearest neighbor searching (NN), and SL and CL were 1-9% less efficient that NN. However, the differences were statistically insignificant. When evaluated with the liberal assessment A, the results suggest that the AL and WM clustering offer better retrieval ability than NN. Assessment B renders the AL and WM clustering better than NN, when recall is considered more important than precision. The results imply that collections in the highly inflectional and agglutinative languages, such as Finnish, may be clustered as the collections in English, provided that documents are appropriately preprocessed

Ectodysplasin has a dual role in ectodermal organogenesis: inhibition of Bmp activity and induction of Shh expression.

Ectodermal organogenesis is regulated by inductive and reciprocal signalling cascades that involve multiple signal molecules in several conserved families. Ectodysplasin-A (Eda), a tumour necrosis factor-like signalling molecule, and its receptor Edar are required for the development of a number of ectodermal organs in vertebrates. In mice, lack of Eda leads to failure in primary hair placode formation and missing or abnormally shaped teeth, whereas mice overexpressing Eda are characterized by enlarged hair placodes and supernumerary teeth and mammary glands. Here, we report two signalling outcomes of the Eda pathway: suppression of bone morphogenetic protein (Bmp) activity and upregulation of sonic hedgehog (Shh) signalling. Recombinant Eda counteracted Bmp4 activity in developing teeth and, importantly, inhibition of BMP activity by exogenous noggin partially restored primary hair placode formation in Eda-deficient skin in vitro, indicating that suppression of Bmp activity was compromised in the absence of Eda. The downstream effects of the Eda pathway are likely to be mediated by transcription factor nuclear factor-kappaB (NF-kappaB), but the transcriptional targets of Edar have remained unknown. Using a quantitative approach, we show in cultured embryonic skin that Eda induced the expression of two Bmp inhibitors, Ccn2/Ctgf (CCN family protein 2/connective tissue growth factor) and follistatin. Moreover, our data indicate that Shh is a likely transcriptional target of Edar, but, unlike noggin, recombinant Shh was unable to rescue primary hair placode formation in Eda-deficient skin explants

AnFlo: Detecting anomalous sensitive information flows in Android apps

Smartphone apps usually have access to sensitive user data such as contacts, geo-location, and account credentials and they might share such data to external entities through the Internet or with other apps. Confidentiality of user data could be breached if there are anomalies in the way sensitive data is handled by an app which is vulnerable or malicious. Existing approaches that detect anomalous sensitive data flows have limitations in terms of accuracy because the definition of anomalous flows may differ for different apps with different functionalities; it is normal for "Health" apps to share heart rate information through the Internet but is anomalous for "Travel" apps. In this paper, we propose a novel approach to detect anomalous sensitive data flows in Android apps, with improved accuracy. To achieve this objective, we first group trusted apps according to the topics inferred from their functional descriptions. We then learn sensitive information flows with respect to each group of trusted apps. For a given app under analysis, anomalies are identified by comparing sensitive information flows in the app against those flows learned from trusted apps grouped under the same topic. In the evaluation, information flow is learned from 11,796 trusted apps. We then checked for anomalies in 596 new (benign) apps and identified 2 previously-unknown vulnerable apps related to anomalous flows. We also analyzed 18 malware apps and found anomalies in 6 of them

Improving Risk Predictions by Preprocessing Imbalanced Credit Data

Imbalanced credit data sets refer to databases in which the class of defaulters is heavily under-represented in comparison to the class of non-defaulters. This is a very common situation in real-life credit scoring applications, but it has still received little attention. This paper investigates whether data resampling can be used to improve the performance of learners built from imbalanced credit data sets, and whether the effectiveness of resampling is related to the type of classifier. Experimental results demonstrate that learning with the resampled sets consistently outperforms the use of the original imbalanced credit data, independently of the classifier used

Improving imbalanced classification by anomaly detection

Although the anomaly detection problem can be considered as an extreme case of class imbalance problem, very few studies consider improving class imbalance classification with anomaly detection ideas. Most data-level approaches in the imbalanced learning domain aim to introduce more information to the original dataset by generating synthetic samples. However, in this paper, we gain additional information in another way, by introducing additional attributes. We propose to introduce the outlier score and four types of samples (safe, borderline, rare, outlier) as additional attributes in order to gain more information on the data characteristics and improve the classification performance. According to our experimental results, introducing additional attributes can improve the imbalanced classification performance in most cases (6 out of 7 datasets). Further study shows that this performance improvement is mainly contributed by a more accurate classification in the overlapping region of the two classes (majority and minority classes). The proposed idea of introducing additional attributes is simple to implement and can be combined with resampling techniques and other algorithmic-level approaches in the imbalanced learning domain.Horizon 2020(H2020)Algorithms and the Foundations of Software technolog

Lrp4 Modulates Extracellular Integration of Cell Signaling Pathways in Development

The extent to which cell signaling is integrated outside the cell is not currently appreciated. We show that a member of the low-density receptor-related protein family, Lrp4 modulates and integrates Bmp and canonical Wnt signalling during tooth morphogenesis by binding the secreted Bmp antagonist protein Wise. Mouse mutants of Lrp4 and Wise exhibit identical tooth phenotypes that include supernumerary incisors and molars, and fused molars. We propose that the Lrp4/Wise interaction acts as an extracellular integrator of epithelial-mesenchymal cell signaling. Wise, secreted from mesenchyme cells binds to BMP's and also to Lrp4 that is expressed on epithelial cells. This binding then results in the modulation of Wnt activity in the epithelial cells. Thus in this context Wise acts as an extracellular signaling molecule linking two signaling pathways. We further show that a downstream mediator of this integration is the Shh signaling pathway

The Edar subfamily in feather placode formation

AbstractA subgroup of the TNF receptor family, composed of Edar, Troy and Xedar, are implicated in the development of ectodermal appendages, such as hair follicles, teeth and sweat glands. We have isolated chicken orthologues of these three receptors and analysed their roles in early feather development. Conservation of protein sequences between mammalian and avian proteins is variable, with avian Edar showing the greatest degree of sequence identity. cXedar differs from its mammalian orthologue in that it contains an intracellular death domain. All three receptors are expressed during early feather morphogenesis and dominant negative forms of each receptor impair the epithelial contribution to feather bud morphogenesis, while the dermal contribution appears unaffected. Hyperactivation of each receptor leads to more widespread assumption of placode fate, though in different regions of the skin. Receptor signaling converges on NF-κB, and inhibiting this transcription factor alters feather bud number and size in a stage-specific manner. Our findings illustrate the roles of these three receptors during avian skin morphogenesis and also suggest that activators of feather placode fate undergo mutual regulation to reach a decision on skin appendage location and size