A postsynaptic PI3K-cII dependent signaling controller for presynaptic homeostatic plasticity.

Presynaptic homeostatic plasticity stabilizes information transfer at synaptic connections in organisms ranging from insect to human. By analogy with principles of engineering and control theory, the molecular implementation of PHP is thought to require postsynaptic signaling modules that encode homeostatic sensors, a set point, and a controller that regulates transsynaptic negative feedback. The molecular basis for these postsynaptic, homeostatic signaling elements remains unknown. Here, an electrophysiology-based screen of the Drosophila kinome and phosphatome defines a postsynaptic signaling platform that includes a required function for PI3K-cII, PI3K-cIII and the small GTPase Rab11 during the rapid and sustained expression of PHP. We present evidence that PI3K-cII localizes to Golgi-derived, clathrin-positive vesicles and is necessary to generate an endosomal pool of PI(3)P that recruits Rab11 to recycling endosomal membranes. A morphologically distinct subdivision of this platform concentrates postsynaptically where we propose it functions as a homeostatic controller for retrograde, trans-synaptic signaling

MMOG/LE: Improving supply chain delivery performance through buyer- supplier collaboration

This article introduces readers to a relatively new self-assessment tool for measuring the readiness and effectiveness of supplier materials management and logistics processes in the automotive industry. The tool, the Material Management Operating Guidelines/Logistics Evaluation (MMOG/ LE), was developed by the Automotive Industry Action Group (AIAG), and Odette International – a European alliance of automotive companies. The article begins with an introduction to the topic of quality and materials management assessment systems. The author’s then report on what they learned about MMOG/LE based on a review of the system and other comparable systems, and based on interviews with OEM’s and tier 1 and 2 auto suppliers that use the system. The article begins with a description of what the MMOG/LE system is, and how it works. The article then has a section comparing MMOG/LE and ISO/TS16949, and then another section comparing MMOG/LE and the SCOR model. The authors then address and comment on various strengths and weaknesses of the MMOG/LE model. Finally, the authors make several recommendations on how the system and processes for managing it could be improved. Overall, the authors find that MMOG/LE is an effective system for improving materials management and logistics performance

A common cardiac sodium channel variant associated with sudden infant death in African Americans, SCN5A S1103Y.

Thousands die each year from sudden infant death syndrome (SIDS). Neither the cause nor basis for varied prevalence in different populations is understood. While 2 cases have been associated with mutations in type Valpha, cardiac voltage-gated sodium channels (SCN5A), the "Back to Sleep" campaign has decreased SIDS prevalence, consistent with a role for environmental influences in disease pathogenesis. Here we studied SCN5A in African Americans. Three of 133 SIDS cases were homozygous for the variant S1103Y. Among controls, 120 of 1,056 were carriers of the heterozygous genotype, which was previously associated with increased risk for arrhythmia in adults. This suggests that infants with 2 copies of S1103Y have a 24-fold increased risk for SIDS. Variant Y1103 channels were found to operate normally under baseline conditions in vitro. As risk factors for SIDS include apnea and respiratory acidosis, Y1103 and wild-type channels were subjected to lowered intracellular pH. Only Y1103 channels gained abnormal function, demonstrating late reopenings suppressible by the drug mexiletine. The variant appeared to confer susceptibility to acidosis-induced arrhythmia, a gene-environment interaction. Overall, homozygous and rare heterozygous SCN5A missense variants were found in approximately 5% of cases. If our findings are replicated, prospective genetic testing of SIDS cases and screening with counseling for at-risk families warrant consideration

Consistent Differential Expression Pattern (CDEP) on microarray to identify genes related to metastatic behavior

<p>Abstract</p> <p>Background</p> <p>To utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP), to identify genes with common differential expression patterns across different datasets.</p> <p>Results</p> <p>We combined False Discovery Rate (FDR) estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as <it>AMIGO2</it>, <it>Gem</it>, and <it>CXCL11 </it>that have not been shown to associate with, but may play roles in, metastasis.</p> <p>Conclusions</p> <p>CDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and insensitivity to data variation commonly associated with microarray experiments.</p> <p><b>Availability</b>: CDEP is implemented in R and freely available at: <url>http://genomebioinfo.musc.edu/CDEP/</url></p> <p><b>Contact</b>: [email protected]</p

Signaling network prediction by the Ontology Fingerprint enhanced Bayesian network

Abstract Background Despite large amounts of available genomic and proteomic data, predicting the structure and response of signaling networks is still a significant challenge. While statistical method such as Bayesian network has been explored to meet this challenge, employing existing biological knowledge for network prediction is difficult. The objective of this study is to develop a novel approach that integrates prior biological knowledge in the form of the Ontology Fingerprint to infer cell-type-specific signaling networks via data-driven Bayesian network learning; and to further use the trained model to predict cellular responses. Results We applied our novel approach to address the Predictive Signaling Network Modeling challenge of the fourth (2009) Dialog for Reverse Engineering Assessment's and Methods (DREAM4) competition. The challenge results showed that our method accurately captured signal transduction of a network of protein kinases and phosphoproteins in that the predicted protein phosphorylation levels under all experimental conditions were highly correlated (R2 = 0.93) with the observed results. Based on the evaluation of the DREAM4 organizer, our team was ranked as one of the top five best performers in predicting network structure and protein phosphorylation activity under test conditions. Conclusions Bayesian network can be used to simulate the propagation of signals in cellular systems. Incorporating the Ontology Fingerprint as prior biological knowledge allows us to efficiently infer concise signaling network structure and to accurately predict cellular responses.http://deepblue.lib.umich.edu/bitstream/2027.42/109490/1/12918_2012_Article_989.pd

Multisymplectic Geometry and Multisymplectic Preissman Scheme for the KP Equation

The multisymplectic structure of the KP equation is obtained directly from the variational principal. Using the covariant De Donder-Weyl Hamilton function theories, we reformulate the KP equation to the multisymplectic form which proposed by Bridges. From the multisymplectic equation, we can derive a multisymplectic numerical scheme of the KP equation which can be simplified to multisymplectic forty-five points scheme.Comment: 17 papges, 8 figure

Structural Basis for VEGF-C Binding to Neuropilin-2 and Sequestration by a Soluble Splice Form

SummaryVascular endothelial growth factor C (VEGF-C) is a potent lymphangiogenic cytokine that signals via the coordinated action of two cell surface receptors, Neuropilin-2 (Nrp2) and VEGFR-3. Diseases associated with both loss and gain of VEGF-C function, lymphedema and cancer, respectively, motivate studies of VEGF-C/Nrp2 binding and inhibition. Here, we demonstrate that VEGF-C binding to Nrp2 is regulated by C-terminal proteolytic maturation. The structure of the VEGF-C C terminus in complex with the ligand binding domains of Nrp2 demonstrates that a cryptic Nrp2 binding motif is released upon proteolysis, allowing specific engagement with the b1 domain of Nrp2. Based on the identified structural requirements for Nrp2 binding to VEGF-C, we hypothesized that the endogenous secreted splice form of Nrp2, s9Nrp2, may function as a selective inhibitor of VEGF-C. We find that s9Nrp2 forms a stable dimer that potently inhibits VEGF-C/Nrp2 binding and cellular signaling. These data provide critical insight into VEGF-C/Nrp2 binding and inhibition

Obesity-Induced Colorectal Cancer Is Driven by Caloric Silencing of the Guanylin-GUCY2C Paracrine Signaling Axis.

Obesity is a well-known risk factor for colorectal cancer but precisely how it influences risks of malignancy remains unclear. During colon cancer development in humans or animals, attenuation of the colonic cell surface receptor guanylyl cyclase C (GUCY2C) that occurs due to loss of its paracrine hormone ligand guanylin contributes universally to malignant progression. In this study, we explored a link between obesity and GUCY2C silencing in colorectal cancer. Using genetically engineered mice on different diets, we found that diet-induced obesity caused a loss of guanylin expression in the colon with subsequent GUCY2C silencing, epithelial dysfunction, and tumorigenesis. Mechanistic investigations revealed that obesity reversibly silenced guanylin expression through calorie-dependent induction of endoplasmic reticulum stress and the unfolded protein response in intestinal epithelial cells. In transgenic mice, enforcing specific expression of guanylin in intestinal epithelial cells restored GUCY2C signaling, eliminating intestinal tumors associated with a high calorie diet. Our findings show how caloric suppression of the guanylin-GUCY2C signaling axis links obesity to negation of a universal tumor suppressor pathway in colorectal cancer, suggesting an opportunity to prevent colorectal cancer in obese patients through hormone replacement with the FDA-approved oral GUCY2C ligand linaclotide

Molecular cloning and characterization of a new peroxidase gene (OvRCI) from Orychophragmus violaceus

A new peroxidase gene from Orychophragmus violaceus was cloned. The full-length cDNA of O.violaceus peroxidase gene (OvRCI, GenBank. Acc. No. AY428037) was 1220 bp and contained an 1128 bp open reading frame encoding a protein of 375 amino acids. Homology analysis and molecularmodeling revealed that OvRCI strongly resembled other peroxidase genes. Quantitative real-time PCR analysis revealed that it was a constitutively salt-inducible gene and its transcript level was most abundant after 24 h treatment with 200 mmol.L-1 sodium chloride. Our studies suggested that OvRCI was a new member of the family of recently cloned peroxidase genes