Potentials of a Harmonised Database for Agricultural Market Modelling

The study analysed existing databases for agricultural market data on errors and discrepancies and to elaborate the possibilities to harmonise datasets for policy modelling. The study supports DG AGRI in improving quality and timely availability of data for market modelling and ensuring that data from different sources are consistent. This study aims to provide a structure for a consolidated database for policy modelling which does not alter existing databases. Within this report, existing databases are analysed to derive key insights for setting-up a harmonised metabase. As available databases comprise statistical databases as well as scientific model databases, both groups are studied. For the purpose of this study, statistical databases are defined as providers of the information that international institutes receive from their reporters, while the reporters are required to provide harmonised, complete, consistent, and where possible, timely data series for establishing models or other quantitative methods. Nevertheless, a statistical database can also serve as a model database, such as e.g. PS&D. Statistical databases from international institutions (FAO, USDA, Eurostat), as well as model databases (AGLINK/COSIMO, AGMEMOD, CAPRI/CAPSIM, ESIM, FAPRI, GTAP, FARM, IMPACT), were studied to find ways of consolidating data and providing insights that allow for a better comparison of model results. For this reason, various classification schemes used in agricultural statistics were reviewed (country, product, balance item, year, unit), as was the manner in which the different modelling groups have dealt with these classifications in their databases. Besides a common classification, a harmonised database for market modelling purposes will require further efforts to be applied to a consolidation effort for the original data. Such a procedure must be supplemented by methods dealing with completion and balancing.JRC.J.5-Agriculture and Life Sciences in the Econom

Pyruvate kinase M2-specific siRNA induces apoptosis and tumor regression

Online supplemental material is available at http://www.jem.org/cgi/content/full/jem.20111487/DC1.The development of cancer-specific therapeutics has been limited because most healthy cells and cancer cells depend on common pathways. Pyruvate kinase (PK) exists in M1 (PKM1) and M2 (PKM2) isoforms. PKM2, whose expression in cancer cells results in aerobic glycolysis and is suggested to bestow a selective growth advantage, is a promising target. Because many oncogenes impart a common alteration in cell metabolism, inhibition of the M2 isoform might be of broad applicability. We show that several small interfering (si) RNAs designed to target mismatches between the M2 and M1 isoforms confer specific knockdown of the former, resulting in decreased viability and increased apoptosis in multiple cancer cell lines but less so in normal fibroblasts or endothelial cells. In vivo delivery of siPKM2 additionally causes substantial tumor regression of established xenografts. Our results suggest that the inherent nucleotide-level specificity of siRNA can be harnessed to develop therapeutics that target isoform-specific exons in genes exhibiting differential splicing patterns in various cell types.MIT-Harvard Center for Cancer Nanotechnology ExcellenceNational Cancer Institute (U.S.) (Grant U54 CA151884)Marie D. and Pierre Casimir-Lambert FundNational Cancer Institute (U.S.) (Cancer Center Support (core) grant P30-CA14051

Contrast-enhanced micro-CT imaging in murine carotid arteries : a new protocol for computing wall shear stress

Background: Wall shear stress (WSS) is involved in the pathophysiology of atherosclerosis. The correlation between WSS and atherosclerosis can be investigated over time using a WSS-manipulated atherosclerotic mouse model. To determine WSS in vivo, detailed 3D geometry of the vessel network is required. However, a protocol to reconstruct 3D murine vasculature using this animal model is lacking. In this project, we evaluated the adequacy of eXIA 160, a small animal contrast agent, for assessing murine vascular network on micro-CT. Also, a protocol was established for vessel geometry segmentation and WSS analysis. Methods: A tapering cast was placed around the right common carotid artery (RCCA) of ApoE(-/-) mice (n = 8). Contrast-enhanced micro-CT was performed using eXIA 160. An innovative local threshold-based segmentation procedure was implemented to reconstruct 3D geometry of the RCCA. The reconstructed RCCA was compared to the vessel geometry using a global threshold-based segmentation method. Computational fluid dynamics was applied to compute the velocity field and WSS distribution along the RCCA. Results: eXIA 160-enhanced micro-CT allowed clear visualization and assessment of the RCCA in all eight animals. No adverse biological effects were observed from the use of eXIA 160. Segmentation using local threshold values generated more accurate RCCA geometry than the global threshold-based approach. Mouse-specific velocity data and the RCCA geometry generated 3D WSS maps with high resolution, enabling quantitative analysis of WSS. In all animals, we observed low WSS upstream of the cast. Downstream of the cast, asymmetric WSS patterns were revealed with variation in size and location between animals. Conclusions: eXIA 160 provided good contrast to reconstruct 3D vessel geometry and determine WSS patterns in the RCCA of the atherosclerotic mouse model. We established a novel local threshold-based segmentation protocol for RCCA reconstruction and WSS computation. The observed differences between animals indicate the necessity to use mouse-specific data for WSS analysis. For our future work, our protocol makes it possible to study in vivo WSS longitudinally over a growing plaque

Contrast-enhanced micro-CT imaging in murine carotid arteries: A new protocol for computing wall shear stress

Background: Wall shear stress (WSS) is involved in the pathophysiology of atherosclerosis. The correlation between WSS and atherosclerosis can be investigated over time using a WSS-manipulated atheroscleroti

Cytoplasmic p53 couples oncogene-driven glucose metabolism to apoptosis and is a therapeutic target in glioblastoma.

Cross-talk among oncogenic signaling and metabolic pathways may create opportunities for new therapeutic strategies in cancer. Here we show that although acute inhibition of EGFR-driven glucose metabolism induces only minimal cell death, it lowers the apoptotic threshold in a subset of patient-derived glioblastoma (GBM) cells. Mechanistic studies revealed that after attenuated glucose consumption, Bcl-xL blocks cytoplasmic p53 from triggering intrinsic apoptosis. Consequently, targeting of EGFR-driven glucose metabolism in combination with pharmacological stabilization of p53 with the brain-penetrant small molecule idasanutlin resulted in synthetic lethality in orthotopic glioblastoma xenograft models. Notably, neither the degree of EGFR-signaling inhibition nor genetic analysis of EGFR was sufficient to predict sensitivity to this therapeutic combination. However, detection of rapid inhibitory effects on [18F]fluorodeoxyglucose uptake, assessed through noninvasive positron emission tomography, was an effective predictive biomarker of response in vivo. Together, these studies identify a crucial link among oncogene signaling, glucose metabolism, and cytoplasmic p53, which may potentially be exploited for combination therapy in GBM and possibly other malignancies

MiR-122 targets pyruvate kinase M2 and affects metabolism of hepatocellular carcinoma

10.1371/journal.pone.0086872PLoS ONE91-POLN

Models of Somatic Hypermutation Targeting and Substitution Based on Synonymous Mutations from High-Throughput Immunoglobulin Sequencing Data

Analyses of somatic hypermutation (SHM) patterns in B cell immunoglobulin (Ig) sequences contribute to our basic understanding of adaptive immunity, and have broad applications not only for understanding the immune response to pathogens, but also to determining the role of SHM in autoimmunity and B cell cancers. Although stochastic, SHM displays intrinsic biases that can confound statistical analysis, especially when combined with the particular codon usage and base composition in Ig sequences. Analysis of B cell clonal expansion, diversification, and selection processes thus critically depends on an accurate background model for SHM micro-sequence targeting (i.e., hot/cold-spots) and nucleotide substitution. Existing models are based on small numbers of sequences/mutations, in part because they depend on data from non-coding regions or non-functional sequences to remove the confounding influences of selection. Here, we combine high-throughput Ig sequencing with new computational analysis methods to produce improved models of SHM targeting and substitution that are based only on synonymous mutations, and are thus independent of selection. The resulting “S5F” models are based on 806,860 Synonymous mutations in 5-mer motifs from 1,145,182 Functional sequences and account for dependencies on the adjacent four nucleotides (two bases upstream and downstream of the mutation). The estimated profiles can explain almost half of the variance in observed mutation patterns, and clearly show that both mutation targeting and substitution are significantly influenced by neighboring bases. While mutability and substitution profiles were highly conserved across individuals, the variability across motifs was found to be much larger than previously estimated. The model and method source code are made available at http://clip.med.yale.edu/SH

A PHGDH inhibitor reveals coordination of serine synthesis and one-carbon unit fate

Serine is a both a proteinogenic amino acid and the source of one-carbon units essential for de novo purine and deoxythymidine synthesis. In the canonical glucose-derived serine synthesis pathway, Homo sapiens phosphoglycerate dehydrogenase (PHGDH) catalyzes the first, ratelimiting step. Genetic loss of PHGDH is toxic towards PHGDH-overexpressing breast cancer cell lines even in the presence of exogenous serine. Here, we use a quantitative high-throughput screen to identify small molecule PHGDH inhibitors. These compounds reduce the production of glucose-derived serine in cells and suppress the growth of PHGDH-dependent cancer cells in culture and in orthotopic xenograft tumors. Surprisingly, PHGDH inhibition reduced the incorporation into nucleotides of one-carbon units from glucose-derived and exogenous serine. We conclude that glycolytic serine synthesis coordinates the use of one-carbon units from endogenous and exogenous serine in nucleotide synthesis, and suggest that one-carbon unit wasting may contribute to the efficacy of PHGDH inhibitors in vitro and in vivo.Damon Runyon Cancer Research Foundation (Sally Gordon Fellowship DRG-112-12)United States. Dept. of Defense. Breast Cancer Research Program (Postdoctoral Fellowship BC120208)American Society for Radiation Oncology (Resident Seed Grant RA-2011-1)European Molecular Biology Organization (Long-Term Fellowship)National Institutes of Health (U.S.) (R03 DA034602-01A1, R01 CA129105, R01 CA103866, and R37 AI047389)United States. Department of Defense (W81XWH-14-PRCRP-IA)Alexander and Margaret Stewart Trus