An Evolutionary Optimization Approach to Risk Parity Portfolio Selection

In this paper we present an evolutionary optimization approach to solve the risk parity portfolio selection problem. While there exist convex optimization approaches to solve this problem when long-only portfolios are considered, the optimization problem becomes non-trivial in the long-short case. To solve this problem, we propose a genetic algorithm as well as a local search heuristic. This algorithmic framework is able to compute solutions successfully. Numerical results using real-world data substantiate the practicability of the approach presented in this paper

Analysis of Tyrosine Kinase Inhibitor-Mediated Decline in Contractile Force in Rat Engineered Heart Tissue

Introduction Left ventricular dysfunction is a frequent and potentially severe side effect of many tyrosine kinase inhibitors (TKI). The mode of toxicity is not identified, but may include impairment of mitochondrial or sarcomeric function, autophagy or angiogenesis, either as an on-target or off-target mechanism. Methods and Results We studied concentration-response curves and time courses for nine TKIs in three-dimensional, force generating engineered heart tissue (EHT) from neonatal rat heart cells. We detected a concentration- and time-dependent decline in contractile force for gefitinib, lapatinib, sunitinib, imatinib, sorafenib, vandetanib and lestaurtinib and no decline in contractile force for erlotinib and dasatinib after 96 hours of incubation. The decline in contractile force was associated with an impairment of autophagy (LC3 Western blot) and appearance of autophagolysosomes (transmission electron microscopy). Conclusion This study demonstrates the feasibility to study TKI-mediated force effects in EHTs and identifies an association between a decline in contractility and inhibition of autophagic flux

Helium poisoning: new procedure for sampling and analysis.

An increasing number of suicidal asphyxiation with a plastic bag with inert gases, and in particular helium (He), have been reported from numerous countries over the last decade. These cases are differently managed and lead to different and variable interpretations. Based on the 12 last cases analysed in the laboratory and on the review of the most recent literature about this topic, updated autopsy guidelines for sampling have been proposed regarding to the samples choice and analytical challenges required by the gaseous state of this substance. Biological samples from airways (lungs lobe) followed by brain and cardiac blood are the best matrices to take during the autopsy to diagnose He exposure. Gaseous samples from trachea, pulmonary bronchi, gastric and cardiac areas are also recommended as alternative samples. The anatomical site of sampling must be carefully detailed, and to this end, forensic imaging constitutes a beneficial tool. Even if He detection is sufficient to conclude to He exposure, He concentrations in samples may be related to He exposure conditions (duration, breathing rate, etc.). A quantification in biological samples could be helpful to document more precisely the case. He concentrations in gaseous samples are reported up to 6.0 μmol/mL (tracheal gas), 2.4 μmol/mL (pulmonary gas), 0.64 μmol/mL (cardiac gas) and 12 μmol/mL (gastric gas). He concentrations in solid/liquid samples are reported up to 28 μmol/g (lungs) and 0.03 μmol/g (cardiac blood). The other matrices usually sampled during autopsy such as urine, peripheral blood, liver, fat matter and kidney appear as not relevant

Negative Regulation of Bone Formation by the Transmembrane Wnt Antagonist Kremen-2

Wnt signalling is a key pathway controlling bone formation in mice and humans. One of the regulators of this pathway is Dkk1, which antagonizes Wnt signalling through the formation of a ternary complex with the transmembrane receptors Krm1/2 and Lrp5/6, thereby blocking the induction of Wnt signalling by the latter ones. Here we show that Kremen-2 (Krm2) is predominantly expressed in bone, and that its osteoblast-specific over-expression in transgenic mice (Col1a1-Krm2) results in severe osteoporosis. Histomorphometric analysis revealed that osteoblast maturation and bone formation are disturbed in Col1a1-Krm2 mice, whereas bone resorption is increased. In line with these findings, primary osteoblasts derived from Col1a1-Krm2 mice display a cell-autonomous differentiation defect, impaired canonical Wnt signalling and decreased production of the osteoclast inhibitory factor Opg. To determine whether the observed effects of Krm2 on bone remodeling are physiologically relevant, we analyzed the skeletal phenotype of 24 weeks old Krm2-deficient mice and observed high bone mass caused by a more than three-fold increase in bone formation. Taken together, these data identify Krm2 as a regulator of bone remodeling and raise the possibility that antagonizing KRM2 might prove beneficial in patients with bone loss disorders

Identification of differentially expressed microRNAs in human male breast cancer

<p>Abstract</p> <p>Background</p> <p>The discovery of small non-coding RNAs and the subsequent analysis of microRNA expression patterns in human cancer specimens have provided completely new insights into cancer biology. Genetic and epigenetic data indicate oncogenic or tumor suppressor function of these pleiotropic regulators. Therefore, many studies analyzed the expression and function of microRNA in human breast cancer, the most frequent malignancy in females. However, nothing is known so far about microRNA expression in male breast cancer, accounting for approximately 1% of all breast cancer cases.</p> <p>Methods</p> <p>The expression of 319 microRNAs was analyzed in 9 primary human male breast tumors and in epithelial cells from 15 male gynecomastia specimens using fluorescence-labeled bead technology. For identification of differentially expressed microRNAs data were analyzed by cluster analysis and selected statistical methods.</p> <p>Expression levels were validated for the most up- or down-regulated microRNAs in this training cohort using real-time PCR methodology as well as in an independent test cohort comprising 12 cases of human male breast cancer.</p> <p>Results</p> <p>Unsupervised cluster analysis separated very well male breast cancer samples and control specimens according to their microRNA expression pattern indicating cancer-specific alterations of microRNA expression in human male breast cancer. miR-21, miR519d, miR-183, miR-197, and miR-493-5p were identified as most prominently up-regulated, miR-145 and miR-497 as most prominently down-regulated in male breast cancer.</p> <p>Conclusions</p> <p>Male breast cancer displays several differentially expressed microRNAs. Not all of them are shared with breast cancer biopsies from female patients indicating male breast cancer specific alterations of microRNA expression.</p

Comparison of evolutionary algorithms in gene regulatory network model inference

Background: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineering of GRNs). However, the nature of these data has made this process very di±cult. At the moment, several methods of discovering qualitative causal relationships between genes with high accuracy from microarray data exist, but large scale quantitative analysis on real biological datasets cannot be performed, to date, as existing approaches are not suitable for real microarray data which are noisy and insu±cient. Results: This paper performs an analysis of several existing evolutionary algorithms for quantitative gene regulatory network modelling. The aim is to present the techniques used and o®er a comprehensive comparison of approaches, under a common framework. Algorithms are applied to both synthetic and real gene expression data from DNA microarrays, and ability to reproduce biological behaviour, scalability and robustness to noise are assessed and compared. Conclusions: Presented is a comparison framework for assessment of evolutionary algorithms, used to infer gene regulatory networks. Promising methods are identi¯ed and a platform for development of appropriate model formalisms is established

Genome-Wide Gene Expression Analysis in Cancer Cells Reveals 3D Growth to Affect ECM and Processes Associated with Cell Adhesion but Not DNA Repair

Cell morphology determines cell behavior, signal transduction, protein-protein interaction, and responsiveness to external stimuli. In cancer, these functions profoundly contribute to resistance mechanisms to radio- and chemotherapy. With regard to this aspect, this study compared the genome wide gene expression in exponentially growing cell lines from different tumor entities, lung carcinoma and squamous cell carcinoma, under more physiological three-dimensional (3D) versus monolayer cell culture conditions. Whole genome cDNA microarray analysis was accomplished using the Affymetrix HG U133 Plus 2.0 gene chip. Significance analysis of microarray (SAM) and t-test analysis revealed significant changes in gene expression profiles of 3D relative to 2D cell culture conditions. These changes affected the extracellular matrix and were mainly associated with biological processes like tissue development, cell adhesion, immune system and defense response in contrast to terms related to DNA repair, which lacked significant alterations. Selected genes were verified by semi-quantitative RT-PCR and Western blotting. Additionally, we show that 3D growth mediates a significant increase in tumor cell radio- and chemoresistance relative to 2D. Our findings show significant gene expression differences between 3D and 2D cell culture systems and indicate that cellular responsiveness to external stress such as ionizing radiation and chemotherapeutics is essentially influenced by differential expression of genes involved in the regulation of integrin signaling, cell shape and cell-cell contact

Establishment and characterization of a new human pancreatic adenocarcinoma cell line with high metastatic potential to the lung

<p>Abstract</p> <p>Background</p> <p>Pancreatic cancer is still associated with devastating prognosis. Real progress in treatment options has still not been achieved. Therefore new models are urgently needed to investigate this deadly disease. As a part of this process we have established and characterized a new human pancreatic cancer cell line.</p> <p>Methods</p> <p>The newly established pancreatic cancer cell line PaCa 5061 was characterized for its morphology, growth rate, chromosomal analysis and mutational analysis of the K-<it>ras</it>, EGFR and p53 genes. Gene-amplification and RNA expression profiles were obtained using an Affymetrix microarray, and overexpression was validated by IHC analysis. Tumorigenicity and spontaneous metastasis formation of PaCa 5061 cells were analyzed in pfp^-/-/rag2^-/-mice. Sensitivity towards chemotherapy was analysed by MTT assay.</p> <p>Results</p> <p>PaCa 5061 cells grew as an adhering monolayer with a doubling time ranging from 30 to 48 hours. M-FISH analyses showed a hypertriploid complex karyotype with multiple numerical and unbalanced structural aberrations. Numerous genes were overexpressed, some of which have previously been implicated in pancreatic adenocarcinoma (GATA6, IGFBP3, IGFBP6), while others were detected for the first time (MEMO1, RIOK3). Specifically highly overexpressed genes (fold change > 10) were identified as EGFR, MUC4, CEACAM1, CEACAM5 and CEACAM6. Subcutaneous transplantation of PaCa 5061 into pfp^-/-/rag2^-/-mice resulted in formation of primary tumors and spontaneous lung metastasis.</p> <p>Conclusion</p> <p>The established PaCa 5061 cell line and its injection into pfp^-/-/rag2^-/-mice can be used as a new model for studying various aspects of the biology of human pancreatic cancer and potential treatment approaches for the disease.</p