Proteínas quinases: características estruturais e inibidores químicos

Protein kinases are one of the largest protein families and they are responsible for regulation of a great number of signal transduction pathways in cells, through the phosphorylation of serine, threonine, or tyrosine residues. Deregulation of these enzymes is associated with several diseases including cancer, diabetes and inflammation. For this reason, specific inhibition of tyrosine or serine/threonine kinases may represent an interesting therapeutic approach. The most important types of protein kinases, their structural features and chemical inhibitors are discussed in this paper. Emphasis is given to the small-molecule drugs that target the ATP-binding sites of these enzymes.

Webometric network analysis : mapping cooperation and geopolitical connections between local government administration on the web

Webben är en enorm källa för information. Innehållet på webbsidorna är en synlig typ av information, men webben innehåller även information av en annan typ, en mera gömd typ i form av sambanden och nätverken som hyperlänkarna skapar mellan webbsajterna och –sidorna som de kopplar ihop. Forskningsområdet webometri ämnar, bland annat, att skapa ny kunskap ur denna gömda information som finns inbyggt i hyperlänkarna samt att skapa förståelse för hurudana fenomen och förhållanden utanför webben kan finnas representerade i hyperlänkarna. Målet med denna forskning var att öka förståelse för användningen av hyperlänkar på webben och speciellt kommunernas användning av hyperlänkar. Denna forskning undersökte hur kommunerna i Egentliga Finland skapade och mottog hyperlänkar samt hurudana nätverk formades av dessa hyperlänkar. Forskningen kartlade nätverk av direkta länkar mellan kommunerna och av samlänkar till och från kommunerna och undersökte ifall dessa nätverk kunde användas för att undersöka geopolitiska förhållanden och samarbete mellan kommunerna i Egentliga Finland. De övergripande forskningsfrågorna som har besvarats i denna forskning är: 1) Från ett webometriskt perspektiv, hur använder kommunerna i Egentliga Finland webben? 2) Kan hyperlänkar (direkta länkar och samlänkar) användas för att kartlägga geopolitiska förhållanden och samarbete mellan kommuner? 3) Vilka är de viktigaste motiveringarna för att skapa länkar mellan, till och från kommunernas webbsajter? Denna forskning kom till ovanligt tydliga resultat för en webometrisk forskning, både när det gäller upptäckta geografiska faktorer som påverkar hyperlänkningarna och de klassificerade motivationerna för att skapa länkarna. Resultaten visade att de direkta hyperlänkarna mellan kommunerna kan användas för att kartlägga geopolitiska förhållanden och samarbete mellan kommunerna för att de direkta länkarna var motiverade av officiella orsaker och de var klart påverkade av distansen mellan kommunerna och av de ekonomiska regionerna. Samlänkningarna in till kommunerna visade sig fungera som ett mått för geografisk likhet mellan kommunerna, medan samlänkningarna ut från kommunerna visade potential för att kunna användas till för att kartlägga kommunernas gemensamma intressen. Forskningen kontribuerade även till utvecklandet av forskningsområdet webometri. En del av de viktigaste kontributionerna av denna forskning var utvecklandet av nya metoder för webometrisk forskning samt att öka kunskap om hur existerande metoder från nätverksanalys kan användas effektivt för webometrisk forskning. Resultaten från denna forskning och de utvecklade metoderna kan användas för snabba kartläggningar av diverse förhållanden mellan olika organisationer och företag genom att använda information gratis tillgängligt på webben.

Mapping of QTLs related with wood quality and developmental characteristics in hybrids (Eucalyptus grandis x Eucalyptus urophylla)

The present work aimed to characterize and identify QTLs for wood quality and growth traits in E. grandis x E. urophylla hybrids. For this purpose a RAPD linkage map was developed for the hybrids (LOD=3 and r=0.40) containing 52 markers and 12 linkage groups. Traits related to wood quality and growth were evaluated in the QTL analyses. QTL analyses were performed using chi-square tests, single-marker, interval mapping and composite interval mapping analyses. All approaches led to the identification of similar QTLs associated with wood density, cellulose pulp yield and percentage of extractives, which were detected and confirmed by both the interval mapping and composite interval mapping methodologies. Some QTLs regions were confirmed only by the composite interval mapping methodology: percentage of soluble lignin, percentage of insoluble lignin, CBH and total height. Overlapping QTLs regions were detected, and these, can be the result of major genes involved in the regulation and control of the growth traits by epistatic interactions. In order to evaluate the effect of early selection using RAPD molecular data, molecular markers adjacent to QTLs were used genotype selection. The analysis of selection differential values suggests that for all the traits the phenotypic selection at seven years should generate larger genetic gains than early selection assisted by molecular markers and the combination of the strategies should elevate the selection efficiency.

Using aster multispectral imagery for mapping woody invasive species in pico da vara natural reserve (Azores Islands, Portugal)

This paper aims to assess the effectiveness of ASTER imagery to support the mapping of Pittosporum undulatum, an invasive woody species, in Pico da Vara Natural Reserve (S. Miguel Island, Archipelago of the Azores, Portugal). This assessment was done by applying K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Maximum Likelihood (MLC) pixel-based supervised classifications to 4 different geographic and remote sensing datasets constituted by the Visible, Near-Infrared (VNIR) and Short Wave Infrared (SWIR) of the ASTER sensor and by digital cartography associated to orography (altitude and "distance to water streams") of which the spatial distribution of Pittosporum undulatum directly depends. Overall, most performed classifications showed a strong agreement and high accuracy. At targeted species level, the two higher classification accuracies were obtained when applying MLC and KNN to the VNIR bands coupled with auxiliary geographic information use. Results improved significantly by including ecology and occurrence information of species (altitude and distance to water streams) in the classification scheme. These results show that the use of ASTER sensor VNIR spectral bands, when coupled to relevant ancillary GIS data, can constitute an effective and low cost approach for the evaluation and continuous assessment of Pittosporum undulatum woodland propagation and distribution within Protected Areas of the Azores Islands.

Mapping of summer crops in the State of Paraná, Brazil, through the 10-day spot vegetation NDVI composites

The search for low subjectivity area estimates has increased the use of remote sensing for agricultural monitoring and crop yield prediction, leading to more flexibility in data acquisition and lower costs comparing to traditional methods such as census and surveys. Low spatial resolution satellite images with higher frequency in image acquisition have shown to be adequate for cropland mapping and monitoring in large areas. The main goal of this study was to map the Summer crops in the State of Paraná, Brazil, using 10-day composition of NDVI SPOT Vegetation data for 2005/2006, 2006/2007 and 2007/2008 cropping seasons. For this, a supervised digital classification method with Parallelepiped algorithm in multitemporal RGB image composites was used, in order to generate masks of Summer cultures for each 10-day composition. Accuracy assessment was performed using Kappa index, overall accuracy and Willmott's concordance index, resulting in good levels of accuracy. This methodology allowed the accomplishment, with free and low resolution data, of the mapping of Summer cultures at State level.

Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil

The objective of this study consisted on mapping the use and soil occupation and evaluation of the quality of irrigation water used in Salto do Lontra, in the state of Paraná, Brazil. Images of the satellite SPOT-5 were used to perform the supervised classification of the Maximum Likelihood algorithm - MAXVER, and the water quality parameters analyzed were pH, EC, HCO3-, Cl-, PO4(3-), NO3-, turbidity, temperature and thermotolerant coliforms in two distinct rainfall periods. The water quality data were subjected to statistical analysis by the techniques of PCA and FA, to identify the most relevant variables in assessing the quality of irrigation water. The characterization of soil use and occupation by the classifier MAXVER allowed the identification of the following classes: crops, bare soil/stubble, forests and urban area. The PCA technique applied to irrigation water quality data explained 53.27% of the variation in water quality among the sampled points. Nitrate, thermotolerant coliforms, temperature, electrical conductivity and bicarbonate were the parameters that best explained the spatial variation of water quality.

Using fraction images derived from modis data for coffee crop mapping

Coffee production was closely linked to the economic development of Brazil and, even today, coffee is an important product of the national agriculture. The State of Minas Gerais currently accounts for 52% of the whole coffee area in Brazil. Remote sensing data can provide information for monitoring and mapping of coffee crops, faster and cheaper than conventional methods. In this context, the objective of this study was to assess the effectiveness of coffee crop mapping in Monte Santo de Minas municipality, Minas Gerais State, Brazil, from fraction images derived from MODIS data, in both dry and rainy seasons. The Spectral Linear Mixing Model was used to derive fraction images of soil, coffee, and water/shade. These fraction images served as input data for the supervised automatic classification using the SVM - Support Vector Machine approach. The best results concerning Overall Accuracy and Kappa Index were obtained in the classification of the dry season, with 67% and 0.41, respectively.