Resource dedication problem in a multi-project environment

There can be different approaches to the management of resources within the context of multi-project scheduling problems. In general, approaches to multiproject scheduling problems consider the resources as a pool shared by all projects. On the other hand, when projects are distributed geographically or sharing resources between projects is not preferred, then this resource sharing policy may not be feasible. In such cases, the resources must be dedicated to individual projects throughout the project durations. This multi-project problem environment is defined here as the resource dedication problem (RDP). RDP is defined as the optimal dedication of resource capacities to different projects within the overall limits of the resources and with the objective of minimizing a predetermined objective function. The projects involved are multi-mode resource constrained project scheduling problems with finish to start zero time lag and non-preemptive activities and limited renewable and nonrenewable resources. Here, the characterization of RDP, its mathematical formulation and two different solution methodologies are presented. The first solution approach is a genetic algorithm employing a new improvement move called combinatorial auction for RDP, which is based on preferences of projects for resources. Two different methods for calculating the projects’ preferences based on linear and Lagrangian relaxation are proposed. The second solution approach is a Lagrangian relaxation based heuristic employing subgradient optimization. Numerical studies demonstrate that the proposed approaches are powerful methods for solving this problem

Intrauterine growth restriction and placental angiogenesis

Background: Vascular endothelial growth factor (VEGF), basic-fibroblast growth factor (b-FGF), and endothelial nitric oxide synthase (eNOS) are factors that take part in placental angiogenesis. They are highly expressed during embryonic and fetal development, especially in the first trimester. In this study, we aimed to investigate the role of placental angiogenesis in the development of intrauterine growth restriction (IUGR) by comparing the levels of expression of VEGF-A, b-FGF, and eNOS in normal-term pregnancy and IUGR placentas.Methods: The expression of VEGF-A, b-FGF, and eNOS was studied using the avidin-biotin-peroxidase method in placental tissues diagnosed as normal (n = 55) and IUGR (n = 55). Results were evaluated in a semi-quantitative manner.Results: The expression of all the markers was significantly higher (p < 0.001) in cytotrophoblasts, syncytiotrophoblasts, extravillous trophoblasts, vascular smooth muscle cells, chorionic villous stromal cells, and villous vascular endothelial cells of the IUGR placentas when compared with those collected from normal-term pregnancies.Conclusion: Increased expression of VEGF-A, b-FGF, and eNOS may be the result of inadequate uteroplacental perfusion, supporting the proposal that abnormal angiogenesis plays a role in the pathophysiology of IUGR. © 2010 Barut et al; licensee BioMed Central Ltd

Spike pattern recognition by supervised classification in low dimensional embedding space

© The Author(s) 2016. This article is published with open access at Springerlink.com under the terms of the Creative Commons Attribution License 4.0, (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.Epileptiform discharges in interictal electroencephalography (EEG) form the mainstay of epilepsy diagnosis and localization of seizure onset. Visual analysis is rater-dependent and time consuming, especially for long-term recordings, while computerized methods can provide efficiency in reviewing long EEG recordings. This paper presents a machine learning approach for automated detection of epileptiform discharges (spikes). The proposed method first detects spike patterns by calculating similarity to a coarse shape model of a spike waveform and then refines the results by identifying subtle differences between actual spikes and false detections. Pattern classification is performed using support vector machines in a low dimensional space on which the original waveforms are embedded by locality preserving projections. The automatic detection results are compared to experts’ manual annotations (101 spikes) on a whole-night sleep EEG recording. The high sensitivity (97 %) and the low false positive rate (0.1 min−1), calculated by intra-patient cross-validation, highlight the potential of the method for automated interictal EEG assessment.Peer reviewedFinal Published versio

Novel tumor suppressive function of Smad4 in serum starvation-induced cell death through PAK1–PUMA pathway

DPC4 (deleted in pancreatic cancer 4)/Smad4 is an essential factor in transforming growth factor (TGF)-β signaling and is also known as a frequently mutated tumor suppressor gene in human pancreatic and colon cancer. However, considering the fact that TGF-β can contribute to cancer progression through transcriptional target genes, such as Snail, MMPs, and epithelial–mesenchymal transition (EMT)-related genes, loss of Smad4 in human cancer would be required for obtaining the TGF-β signaling-independent advantage, which should be essential for cancer cell survival. Here, we provide the evidences about novel role of Smad4, serum-deprivation-induced apoptosis. Elimination of serum can obviously increase the Smad4 expression and induces the cell death by p53-independent PUMA induction. Instead, Smad4-deficient cells show the resistance to serum starvation. Induced Smad4 suppresses the PAK1, which promotes the PUMA destabilization. We also found that Siah-1 and pVHL are involved in PAK1 destabilization and PUMA stabilization. In fact, Smad4-expressed cancer tissues not only show the elevated expression of PAK1, but also support our hypothesis that Smad4 induces PUMA-mediated cell death through PAK1 suppression. Our results strongly suggest that loss of Smad4 renders the resistance to serum-deprivation-induced cell death, which is the TGF-β-independent tumor suppressive role of Smad4

Dysregulation of Cell Polarity Proteins Synergize with Oncogenes or the Microenvironment to Induce Invasive Behavior in Epithelial Cells

Changes in expression and localization of proteins that regulate cell and tissue polarity are frequently observed in carcinoma. However, the mechanisms by which changes in cell polarity proteins regulate carcinoma progression are not well understood. Here, we report that loss of polarity protein expression in epithelial cells primes them for cooperation with oncogenes or changes in tissue microenvironment to promote invasive behavior. Activation of ErbB2 in cells lacking the polarity regulators Scribble, Dlg1 or AF-6, induced invasive properties. This cooperation required the ability of ErbB2 to regulate the Par6/aPKC polarity complex. Inhibition of the ErbB2-Par6 pathway was sufficient to block ErbB2-induced invasion suggesting that two polarity hits may be needed for ErbB2 to promote invasion. Interestingly, in the absence of ErbB2 activation, either a combined loss of two polarity proteins, or exposure of cells lacking one polarity protein to cytokines IL-6 or TNFα induced invasive behavior in epithelial cells. We observed the invasive behavior only when cells were plated on a stiff matrix (Matrigel/Collagen-1) and not when plated on a soft matrix (Matrigel alone). Cells lacking two polarity proteins upregulated expression of EGFR and activated Akt. Inhibition of Akt activity blocked the invasive behavior identifying a mechanism by which loss of polarity promotes invasion of epithelial cells. Thus, we demonstrate that loss of polarity proteins confers phenotypic plasticity to epithelial cells such that they display normal behavior under normal culture conditions but display aggressive behavior in response to activation of oncogenes or exposure to cytokines

Prostate cancer in male BRCA1 and BRCA2 mutation carriers has a more aggressive phenotype

There is a high and rising prevalence of prostate cancer (PRCA) within the male population of the United Kingdom. Although the relative risk of PRCA is higher in male BRCA2 and BRCA1 mutation carriers, the histological characteristics of this malignancy in these groups have not been clearly defined. We present the histopathological findings in the first UK series of BRCA1 and BRCA2 mutation carriers with PRCA. The archived histopathological tissue sections of 20 BRCA1/2 mutation carriers with PRCA were collected from histopathology laboratories in England, Ireland and Scotland. The cases were matched to a control group by age, stage and serum PSA level of PRCA cases diagnosed in the general population. Following histopathological evaluation and re-grading according to current conventional criteria, Gleason scores of PRCA developed by BRCA1/2 mutation carriers were identified to be significantly higher (Gleason scores 8, 9 or 10, P=0.012) than those in the control group. Since BRCA1/2 mutation carrier status is associated with more aggressive disease, it is a prognostic factor for PRCA outcome. Targeting screening to this population may detect disease at an earlier clinical stage which may therefore be beneficial

Key role for ubiquitin protein modification in TGFβ signal transduction

The transforming growth factor β (TGFβ) superfamily of signal transduction molecules plays crucial roles in the regulation of cell behavior. TGFβ regulates gene transcription through Smad proteins and signals via non-Smad pathways. The TGFβ pathway is strictly regulated, and perturbations lead to tumorigenesis. Several pathway components are known to be targeted for proteasomal degradation via ubiquitination by E3 ligases. Smurfs are well known negative regulators of TGFβ, which function as E3 ligases recruited by adaptors such as I-Smads. TGFβ signaling can also be enhanced by E3 ligases, such as Arkadia, that target repressors for degradation. It is becoming clear that E3 ligases often target multiple pathways, thereby acting as mediators of signaling cross-talk. Regulation via ubiquitination involves a complex network of E3 ligases, adaptor proteins, and deubiquitinating enzymes (DUBs), the last-mentioned acting by removing ubiquitin from its targets. Interestingly, also non-degradative ubiquitin modifications are known to play important roles in TGFβ signaling. Ubiquitin modifications thus play a key role in TGFβ signal transduction, and in this review we provide an overview of known players, focusing on recent advances

Computer Simulation of Cellular Patterning Within the Drosophila Pupal Eye

We present a computer simulation and associated experimental validation of assembly of glial-like support cells into the interweaving hexagonal lattice that spans the Drosophila pupal eye. This process of cell movements organizes the ommatidial array into a functional pattern. Unlike earlier simulations that focused on the arrangements of cells within individual ommatidia, here we examine the local movements that lead to large-scale organization of the emerging eye field. Simulations based on our experimental observations of cell adhesion, cell death, and cell movement successfully patterned a tracing of an emerging wild-type pupal eye. Surprisingly, altering cell adhesion had only a mild effect on patterning, contradicting our previous hypothesis that the patterning was primarily the result of preferential adhesion between IRM-class surface proteins. Instead, our simulations highlighted the importance of programmed cell death (PCD) as well as a previously unappreciated variable: the expansion of cells' apical surface areas, which promoted rearrangement of neighboring cells. We tested this prediction experimentally by preventing expansion in the apical area of individual cells: patterning was disrupted in a manner predicted by our simulations. Our work demonstrates the value of combining computer simulation with in vivo experiments to uncover novel mechanisms that are perpetuated throughout the eye field. It also demonstrates the utility of the Glazier–Graner–Hogeweg model (GGH) for modeling the links between local cellular interactions and emergent properties of developing epithelia as well as predicting unanticipated results in vivo