Incremental dimension reduction of tensors with random index

We present an incremental, scalable and efficient dimension reduction technique for tensors that is based on sparse random linear coding. Data is stored in a compactified representation with fixed size, which makes memory requirements low and predictable. Component encoding and decoding are performed on-line without computationally expensive re-analysis of the data set. The range of tensor indices can be extended dynamically without modifying the component representation. This idea originates from a mathematical model of semantic memory and a method known as random indexing in natural language processing. We generalize the random-indexing algorithm to tensors and present signal-to-noise-ratio simulations for representations of vectors and matrices. We present also a mathematical analysis of the approximate orthogonality of high-dimensional ternary vectors, which is a property that underpins this and other similar random-coding approaches to dimension reduction. To further demonstrate the properties of random indexing we present results of a synonym identification task. The method presented here has some similarities with random projection and Tucker decomposition, but it performs well at high dimensionality only (n>10^3). Random indexing is useful for a range of complex practical problems, e.g., in natural language processing, data mining, pattern recognition, event detection, graph searching and search engines. Prototype software is provided. It supports encoding and decoding of tensors of order >= 1 in a unified framework, i.e., vectors, matrices and higher order tensors.Comment: 36 pages, 9 figure

Does the road to happiness depend on the retirement decision? Evidence from Italy

This study estimates the causal effect of retirement decision on well-being in Italy. To do so, the authors exploit the exogenous variation provided by the changes in the eligibility criteria for pensions that were enacted in Italy in 1995 (Dini’s law) and in 1997 (Prodi’s law, from the names of the prime ministers at the time of their introduction). A sizeable and positive impact of retirement decision is found on satisfaction with leisure time and on frequency of meeting friends. Furthermore, the results are generalized, allowing for the estimation of different moments from different data sources

Loss of CSL Unlocks a Hypoxic Response and Enhanced Tumor Growth Potential in Breast Cancer Cells

Notch signaling is an important regulator of stem cell differentiation. All canonical Notch signaling is transmitted through the DNA-binding protein CSL, and hyperactivated Notch signaling is associated with tumor development; thus it may be anticipated that CSL deficiency should reduce tumor growth. In contrast, we report that genetic removal of CSL in breast tumor cells caused accelerated growth of xenografted tumors. Loss of CSL unleashed a hypoxic response during normoxic conditions, manifested by stabilization of the HIF1α protein and acquisition of a polyploid giant-cell, cancer stem cell-like, phenotype. At the transcriptome level, loss of CSL upregulated more than 1,750 genes and less than 3% of those genes were part of the Notch transcriptional signature. Collectively, this suggests that CSL exerts functions beyond serving as the central node in the Notch signaling cascade and reveals a role for CSL in tumorigenesis and regulation of the cellular hypoxic response.</p

Keratins regulate colonic epithelial cell differentiation through the Notch1 signalling pathway

Keratins (K) are intermediate filament proteins important in stress protection and mechanical support of epithelial tissues. K8, K18 and K19 are the main colonic keratins, and K8-knockout (K8(-/-)) mice display a keratin dose-dependent hyperproliferation of colonic crypts and a colitis-phenotype. However, the impact of the loss of K8 on intestinal cell differentiation has so far been unknown. Here we show that K8 regulates Notch1 signalling activity and differentiation in the epithelium of the large intestine. Proximity ligation and immunoprecipitation assays demonstrate that K8 and Notch1 co-localize and interact in cell cultures, and in vivo in the colonic epithelial cells. K8 with its heteropolymeric partner K18 enhance Notch1 protein levels and activity in a dose dependent manner. The levels of the full-length Notch1 receptor (FLN), the Notch1 intracellular domain (NICD) and expression of Notch1 downstream target genes are reduced in the absence of K8, and the K8-dependent loss of Notch1 activity can be rescued with re-expression of K8/K18 in K8-knockout CRISPR/Cas9 Caco-2 cells protein levels. In vivo, K8 deletion with subsequent Notch1 downregulation leads to a shift in differentiation towards a goblet cell and enteroendocrine phenotype from an enterocyte cell fate. Furthermore, the K8(-/-) colonic hyperproliferation results from an increased number of transit amplifying progenitor cells in these mice. K8/K18 thus interact with Notch1 and regulate Notch1 signalling activity during differentiation of the colonic epithelium

In Situ Coupled Electrochemical-Goniometry as a Tool to Reveal Conformational Changes of Charged Peptides

The opportunity to manipulate cell functions by regulating bioactive surfaces is a potentially promising approach for organic bioelectronics. Here, the tuning of the orientation of charged peptides by means of an electrical input observed via optical tensiometry is reported. A stimuli-responsive self-assembled monolayer (SAM) with specially designed charged peptides is used as a model system to switch between two separate hydrophilic states. The underwater contact angle (UCA) technique is used to measure changes in the wetting property of a dichloromethane droplet under electrical stimuli. The observed changes in the UCA of the bio-interface can be understood in terms of a change in the surface energy between the ON and OFF states. Molecular dynamics simulations in an electric field have been performed to verify the hypothesis of the orientational change of the charged peptides upon electrical stimulation. In addition, X-ray photoelectron spectroscopy (XPS) is performed to clarify the stability of the functionalized electrodes. Finally, the possibility of using such a novel switching system as a tool to characterize bioactive surfaces is discussed

Gamma secretase inhibition promotes hypoxic necrosis in mouse pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDA) is a highly lethal disease that is refractory to medical intervention. Notch pathway antagonism has been shown to prevent pancreatic preneoplasia progression in mouse models, but potential benefits in the setting of an established PDA tumor have not been established. We demonstrate that the gamma secretase inhibitor MRK003 effectively inhibits intratumoral Notch signaling in the KPC mouse model of advanced PDA. Although MRK003 monotherapy fails to extend the lifespan of KPC mice, the combination of MRK003 with the chemotherapeutic gemcitabine prolongs survival. Combination treatment kills tumor endothelial cells and synergistically promotes widespread hypoxic necrosis. These results indicate that the paucivascular nature of PDA can be exploited as a therapeutic vulnerability, and the dual targeting of the tumor endothelium and neoplastic cells by gamma secretase inhibition constitutes a rationale for clinical translation

Expression of Nestin by Neural Cells in the Adult Rat and Human Brain

Neurons and glial cells in the developing brain arise from neural progenitor cells (NPCs). Nestin, an intermediate filament protein, is thought to be expressed exclusively by NPCs in the normal brain, and is replaced by the expression of proteins specific for neurons or glia in differentiated cells. Nestin expressing NPCs are found in the adult brain in the subventricular zone (SVZ) of the lateral ventricle and the subgranular zone (SGZ) of the dentate gyrus. While significant attention has been paid to studying NPCs in the SVZ and SGZ in the adult brain, relatively little attention has been paid to determining whether nestin-expressing neural cells (NECs) exist outside of the SVZ and SGZ. We therefore stained sections immunocytochemically from the adult rat and human brain for NECs, observed four distinct classes of these cells, and present here the first comprehensive report on these cells. Class I cells are among the smallest neural cells in the brain and are widely distributed. Class II cells are located in the walls of the aqueduct and third ventricle. Class IV cells are found throughout the forebrain and typically reside immediately adjacent to a neuron. Class III cells are observed only in the basal forebrain and closely related areas such as the hippocampus and corpus striatum. Class III cells resemble neurons structurally and co-express markers associated exclusively with neurons. Cell proliferation experiments demonstrate that Class III cells are not recently born. Instead, these cells appear to be mature neurons in the adult brain that express nestin. Neurons that express nestin are not supposed to exist in the brain at any stage of development. That these unique neurons are found only in brain regions involved in higher order cognitive function suggests that they may be remodeling their cytoskeleton in supporting the neural plasticity required for these functions

Semantically linking molecular entities in literature through entity relationships

Background Text mining tools have gained popularity to process the vast amount of available research articles in the biomedical literature. It is crucial that such tools extract information with a sufficient level of detail to be applicable in real life scenarios. Studies of mining non-causal molecular relations attribute to this goal by formally identifying the relations between genes, promoters, complexes and various other molecular entities found in text. More importantly, these studies help to enhance integration of text mining results with database facts. Results We describe, compare and evaluate two frameworks developed for the prediction of non-causal or 'entity' relations (REL) between gene symbols and domain terms. For the corresponding REL challenge of the BioNLP Shared Task of 2011, these systems ranked first (57.7% F-score) and second (41.6% F-score). In this paper, we investigate the performance discrepancy of 16 percentage points by benchmarking on a related and more extensive dataset, analysing the contribution of both the term detection and relation extraction modules. We further construct a hybrid system combining the two frameworks and experiment with intersection and union combinations, achieving respectively high-precision and high-recall results. Finally, we highlight extremely high-performance results (F-score > 90%) obtained for the specific subclass of embedded entity relations that are essential for integrating text mining predictions with database facts. Conclusions The results from this study will enable us in the near future to annotate semantic relations between molecular entities in the entire scientific literature available through PubMed. The recent release of the EVEX dataset, containing biomolecular event predictions for millions of PubMed articles, is an interesting and exciting opportunity to overlay these entity relations with event predictions on a literature-wide scale