Contribution de l'écologie du paysage à la diversification des agroécosystèmes à des fins de phytoprotection

Cet article de synthèse établit un lien entre la diversification des systèmes agricoles et le contrôle naturel des insectes ravageurs d'une part, et l'écologie du paysage d'autre part. L'analyse de la revue de littérature réalisée suggère que cette jeune science et le recours à la géomatique pourraient non seulement permettre de concevoir de nouvelles approches en recherche, mais aussi de participer à l'aménagement des agroécosystèmes à des fins de phytoprotection dans une perspective d'agriculture durable au Québec.In this review we establish a link between the diversification of agricultural systems and natural control of crop pests in one hand, and in the other hand the potential contribution of a young science, landscape ecology, which associated with geomatic, can elaborate new ways in research and take part in managing agroecosystems for crop protection in a sustainable manner in Québec

Targeted glycoproteomic identification of cancer cell glycosylation

GalMBP is a fragment of serum mannose-binding protein that has been modified to create a probe for galactose-containing ligands. Glycan array screening demonstrated that the carbohydrate-recognition domain of GalMBP selectively binds common groups of tumor-associated glycans, including Lewis-type structures and T antigen, suggesting that engineered glycan-binding proteins such as GalMBP represent novel tools for the characterization of glycoproteins bearing tumor-associated glycans. Blotting of cell extracts and membranes from MCF7 breast cancer cells with radiolabeled GalMBP was used to demonstrate that it binds to a selected set of high molecular weight glycoproteins that could be purified from MCF7 cells on an affinity column constructed with GalMBP. Proteomic and glycomic analysis of these glycoproteins by mass spectrometry showed that they are forms of CD98hc that bear glycans displaying heavily fucosylated termini, including Lewisx and Lewisy structures. The pool of ligands was found to include the target ligands for anti-CD15 antibodies, which are commonly used to detect Lewisx antigen on tumors, and for the endothelial scavenger receptor C-type lectin, which may be involved in tumor metastasis through interactions with this antigen. A survey of additional breast cancer cell lines reveals that there is wide variation in the types of glycosylation that lead to binding of GalMBP. Higher levels of binding are associated either with the presence of outer-arm fucosylated structures carried on a variety of different cell surface glycoproteins or with the presence of high levels of the mucin MUC1 bearing T antigen

Interaction proteomics of synapse protein complexes

The brain integrates complex types of information, and executes a wide range of physiological and behavioral processes. Trillions of tiny organelles, the synapses, are central to neuronal communication and information processing in the brain. Synaptic transmission involves an intricate network of synaptic proteins that forms the molecular machinery underlying transmitter release, activation, and modulation of transmitter receptors and signal transduction cascades. These processes are dynamically regulated and underlie neuroplasticity, crucial to learning and memory formation. In recent years, interaction proteomics has increasingly been used to elucidate the constituents of synaptic protein complexes. Unlike classic hypothesis-based assays, interaction proteomics detects both known and novel interactors without bias. In this trend article, we focus on the technical aspects of recent proteomics to identify synapse protein complexes, and the complementary methods used to verify the protein–protein interaction. Moreover, we discuss the experimental feasibility of performing global analysis of the synapse protein interactome

Minería de datos para el descubrimiento de patrones en enfermedades respiratorias en Bogotá, Colombia

Trabajo de InvestigaciónEl presente proyecto se basa en la aplicación de minería de datos mediante el algoritmo de clustering K- means que permita la generación de un modelo descriptivo con el análisis de los datos y con el objetivo de identificar posibles comportamientos en enfermedades respiratorias en la ciudad de Bogotá. El conjunto de clústeres generados por la herramienta RapidMiner es la recopilación de datos de un periodo de cinco años de 2012 a 2016, en donde se contemplan el número de casos asociados a 184 diagnósticos de enfermedades respiratorias y la edad de los pacientes corresponde de 0 a 5 años.Trabajo de Investigación1. GENERALIDADES 2. OBJETIVOS 3. JUSTIFICACIÓN 4. DELIMITACIÓN 5. MARCO REFERENCIAL 6. METODOLOGÍA 7. FUENTES DE EXTRACCIÓN Y SUS VARIABLES 8. DISEÑO 9. SELECCIÓN DE ALGORITMOS DE CLUSTERING 10. RECONOCER PATRONES A PARTIR DE LA INFORMACIÓN RECOPILADA 11. CONCLUSIONES 12. TRABAJOS FUTUROS 13. REFERENCIAS BIBLIOGRÁFICAS 14. ANEXOSPregradoIngeniero de Sistema

new technologies for the sustainable management and planning of rural land and environment

New technologies could be adequately introduced for an improved analysis aimed to the sustainable management and planning of the rural land, as well as its environment and landscape. Nowadays, this analysis is easier and more complete through the use of powerful and reliable tools. Several changes can be considered to be as models of territorial development, useful for an appropriate planning of the human interventions in a rural area. Remote sensing techniques could be employed for the monitoring of agricultural land variation, while Geographical Information Systems are excellent tools for landscape modeling and three-dimensional analysis. In this chapter, land-use changes in a rural area located in southern Italy were analyzed by comparing some historical cartographic supports with modern maps, in order to evaluate the morphological and vegetation variations of the agroforestry land during time. Moreover, a landscape analysis was conducted through the implementation of digital terrain models, which were enriched by draping land cover pictures over them. These elaborations finally enabled an evaluation in a scenic way of the aesthetic quality of the agroforestry landscape, allowing a virtual jump back to time periods when digital aerial photography was not yet even possible. This multi-temporal analysis with the support of GIS techniques revealed to have a great potential for assessing and managing landscape diversity and changes of vegetation, as well as for planning sound interventions over the landscape structures

Chronic Oral Infection with Porphyromonas gingivalis Accelerates Atheroma Formation by Shifting the Lipid Profile

BACKGROUND: Recent studies have suggested that periodontal disease increases the risk of atherothrombotic disease. Atherosclerosis has been characterized as a chronic inflammatory response to cholesterol deposition in the arteries. Although several studies have suggested that certain periodontopathic bacteria accelerate atherogenesis in apolipoprotein E-deficient mice, the mechanistic link between cholesterol accumulation and periodontal infection-induced inflammation is largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: We orally infected C57BL/6 and C57BL/6.KOR-Apoe(shl) (B6.Apoeshl) mice with Porphyromonas gingivalis, which is a representative periodontopathic bacterium, and evaluated atherogenesis, gene expression in the aorta and liver and systemic inflammatory and lipid profiles in the blood. Furthermore, the effect of lipopolysaccharide (LPS) from P. gingivalis on cholesterol transport and the related gene expression was examined in peritoneal macrophages. Alveolar bone resorption and elevation of systemic inflammatory responses were induced in both strains. Despite early changes in the expression of key genes involved in cholesterol turnover, such as liver X receptor and ATP-binding cassette A1, serum lipid profiles did not change with short-term infection. Long-term infection was associated with a reduction in serum high-density lipoprotein (HDL) cholesterol but not with the development of atherosclerotic lesions in wild-type mice. In B6.Apoeshl mice, long-term infection resulted in the elevation of very low-density lipoprotein (VLDL), LDL and total cholesterols in addition to the reduction of HDL cholesterol. This shift in the lipid profile was concomitant with a significant increase in atherosclerotic lesions. Stimulation with P. gingivalis LPS induced the change of cholesterol transport via targeting the expression of LDL receptor-related genes and resulted in the disturbance of regulatory mechanisms of the cholesterol level in macrophages. CONCLUSIONS/SIGNIFICANCE: Periodontal infection itself does not cause atherosclerosis, but it accelerates it by inducing systemic inflammation and deteriorating lipid metabolism, particularly when underlying hyperlidemia or susceptibility to hyperlipidemia exists, and it may contribute to the development of coronary heart disease

Multiple Statistical Analysis Techniques Corroborate Intratumor Heterogeneity in Imaging Mass Spectrometry Datasets of Myxofibrosarcoma

MALDI mass spectrometry can generate profiles that contain hundreds of biomolecular ions directly from tissue. Spatially-correlated analysis, MALDI imaging MS, can simultaneously reveal how each of these biomolecular ions varies in clinical tissue samples. The use of statistical data analysis tools to identify regions containing correlated mass spectrometry profiles is referred to as imaging MS-based molecular histology because of its ability to annotate tissues solely on the basis of the imaging MS data. Several reports have indicated that imaging MS-based molecular histology may be able to complement established histological and histochemical techniques by distinguishing between pathologies with overlapping/identical morphologies and revealing biomolecular intratumor heterogeneity. A data analysis pipeline that identifies regions of imaging MS datasets with correlated mass spectrometry profiles could lead to the development of novel methods for improved diagnosis (differentiating subgroups within distinct histological groups) and annotating the spatio-chemical makeup of tumors. Here it is demonstrated that highlighting the regions within imaging MS datasets whose mass spectrometry profiles were found to be correlated by five independent multivariate methods provides a consistently accurate summary of the spatio-chemical heterogeneity. The corroboration provided by using multiple multivariate methods, efficiently applied in an automated routine, provides assurance that the identified regions are indeed characterized by distinct mass spectrometry profiles, a crucial requirement for its development as a complementary histological tool. When simultaneously applied to imaging MS datasets from multiple patient samples of intermediate-grade myxofibrosarcoma, a heterogeneous soft tissue sarcoma, nodules with mass spectrometry profiles found to be distinct by five different multivariate methods were detected within morphologically identical regions of all patient tissue samples. To aid the further development of imaging MS based molecular histology as a complementary histological tool the Matlab code of the agreement analysis, instructions and a reduced dataset are included as supporting information

Simultaneous Quantitation of Amino Acid Mixtures using Clustering Agents

A method that uses the abundances of large clusters formed in electrospray ionization to determine the solution-phase molar fractions of amino acids in multi-component mixtures is demonstrated. For solutions containing either four or 10 amino acids, the relative abundances of protonated molecules differed from their solution-phase molar fractions by up to 30-fold and 100-fold, respectively. For the four-component mixtures, the molar fractions determined from the abundances of larger clusters consisting of 19 or more molecules were within 25% of the solution-phase molar fractions, indicating that the abundances and compositions of these clusters reflect the relative concentrations of these amino acids in solution, and that ionization and detection biases are significantly reduced. Lower accuracy was obtained for the 10-component mixtures where values determined from the cluster abundances were typically within a factor of three of their solution molar fractions. The lower accuracy of this method with the more complex mixtures may be due to specific clustering effects owing to the heterogeneity as a result of significantly different physical properties of the components, or it may be the result of lower S/N for the more heterogeneous clusters and not including the low-abundance more highly heterogeneous clusters in this analysis. Although not as accurate as using traditional standards, this clustering method may find applications when suitable standards are not readily available