188 resultados para Plant selection


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A major challenge in this era of rapid climate change is to predict changes in species distributions and their impacts on ecosystems, and, if necessary, to recommend management strategies for maintenance of biodiversity or ecosystem services. Biological invasions, studied in most biomes of the world, can provide useful analogs for some of the ecological consequences of species distribution shifts in response to climate change. Invasions illustrate the adaptive and interactive responses that can occur when species are confronted with new environmental conditions. Invasion ecology complements climate change research and provides insights into the following questions: i) how will species distributions respond to climate change? ii) how will species movement affect recipient ecosystems? and iii) should we, and if so how can we, manage species and ecosystems in the face of climate change? Invasion ecology demonstrates that a trait-based approach can help to predict spread speeds and impacts on ecosystems, and has the potential to predict climate change impacts on species ranges and recipient ecosystems. However, there is a need to analyse traits in the context of life-history and demography, the stage in the colonisation process (e.g., spread, establishment or impact), the distribution of suitable habitats in the landscape, and the novel abiotic and biotic conditions under which those traits are expressed. As is the case with climate change, invasion ecology is embedded within complex societal goals. Both disciplines converge on similar questions of "when to intervene?" and "what to do?" which call for a better understanding of the ecological processes and social values associated with changing ecosystems.

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During their development, immature CD4+ CD8+ thymocytes become committed to either the CD4 or CD8 lineage. Subsequent complete maturation of CD4+ and CD8+ cells requires a molecular match of the expressed coreceptor and the MHC specificity of the TCR. The final size of the mature CD4+ and CD8+ thymic compartments is therefore determined by a combination of lineage commitment and TCR-mediated selection. In humans and mice, the relative size of CD4+ and CD8+ peripheral T cell compartments shows marked genetic variability. We show here that genetic variations in thymic lineage commitment, rather than TCR-mediated selection processes, are responsible for the distinct CD4/CD8 ratios observed in common inbred mouse strains. Genetic variations in the regulation of lineage commitment open new ways to analyze this process and to identify the molecules involved.

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Heart transplantation (HTx) started in 1987 at two university hospitals (CHUV, HUG) in the western part of Switzerland, with 223 HTx performed at the CHUV until December 2010. Between 1987 and 2003, 106 HTx were realized at the HUG resulting in a total of 329 HTx in the western part of Switzerland. After the relocation of organ transplantation activity in the western part of Switzerland in 2003, the surgical part and the early postoperative care of HTx remained limited to the CHUV. However, every other HTx activity are pursued at the two university hospitals (CHUV, HUG). This article summarizes the actual protocols for selection and pre-transplant follow-up of HTx candidates in the western part of Switzerland, permitting a uniform structure of pretransplant follow-up in the western part of Switzerland.

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Presented here is a cell-suspension model for positive selection using thymocytes from alphabeta-TCR (H-2Db-restricted) transgenic mice specific to the lymphocytic choriomeningitis virus (LCMV) on a nonselecting MHC background (H-2d or TAP-1 -/-), cocultured with freshly isolated adult thymus stromal cells of the selecting MHC type. The thymic stromal cells alone induced positive selection of functional CD4- CD8+ cells whose kinetics and efficiency were enhanced by nominal peptide. Fibroblasts expressing the selecting MHC alone did not induce positive selection; however, together with nonselecting stroma and nominal peptide, there was inefficient positive. These results suggest multiple signaling in positive selection with selection events able to occur on multiple-cell types. The ease with which this model can be manipulated should greatly facilitate the resolution of the mechanisms of positive selection in normal and pathological states.

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T cells belong to two distinct lineages expressing either alpha beta or gamma delta TCR. During alpha beta T cell development, it is clearly established that productive rearrangement at the TCR beta locus in immature precursor cells leads to the expression of a pre-TCR complex. Signaling through the pre-TCR results in the selective proliferation and maturation of TCR beta+ cells, a process that is known as beta-selection. However, the potential role of beta-selection during gamma delta T cell development is controversial. Whereas PCR-RFLP and sequencing techniques have provided evidence for a bias toward in-frame VDJ beta rearrangements in gamma delta cells (consistent with beta-selection), gamma delta cells apparently develop normally in mice that are unable to assemble a pre-TCR complex due to a deficiency in TCR beta or pT alpha genes. In this report, we have directly addressed the physiologic significance of beta-selection during gamma delta cell development in normal mice by quantitating intracellular TCR beta protein in gamma delta cells and correlating its presence with cell cycle status. Our results indicate that beta-selection plays a significant (although limited) role in gamma delta cell development by selectively amplifying a minor subset of gamma delta precursor cells with productively rearranged TCR beta genes.

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In the mid-to long-term, resource constraints will force society to cover a significant share of the future demand for fuels, materials and chemicals by renewable resources. This trend is already visible in the increasing conversion of carbohydrates and plant oils to fuels, chemicals, and polymers. In this perspective, we discuss current efforts and ideas to produce platform chemicals and polymers directly in transgenic plants.

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OBJECTIVE: To test a method that allows automatic set-up of the ventilator controls at the onset of ventilation. DESIGN: Prospective randomized crossover study. SETTING: ICUs in one adult and one children's hospital in Switzerland. PATIENTS: Thirty intubated stable, critically ill patients (20 adults and 10 children). INTERVENTIONS: The patients were ventilated during two 20-min periods using a modified Hamilton AMADEUS ventilator. During the control period the ventilator settings were chosen immediately prior to the study. During the other period individual settings were automatically determined by the ventilatior (AutoInit). MEASUREMENTS AND RESULTS: Pressure, flow, and instantaneous CO2 concentration were measured at the airway opening. From these measurements, series dead space (V(DS)), expiratory time constant (RC), tidal volume (VT, total respiratory frequency (f(tot), minute ventilation (MV), and maximal and mean airway pressure (Paw, max and Paw, mean) were calculated. Arterial blood gases were analyzed at the end of each period. Paw, max was significantly less with the AutoInit ventilator settings while f(tot) was significantly greater (P < 0.05). The other values were not statistically significant. CONCLUSIONS: The AutoInit ventilator settings, which were automatically derived, were acceptable for all patients for a period of 20 min and were not found to be inferior to the control ventilator settings. This makes the AutoInit method potentially useful as an automatic start-up procedure for mechanical ventilation.

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The manipulation of DNA is routine practice in botanical research and has made a huge impact on plant breeding, biotechnology and biodiversity evaluation. DNA is easy to extract from most plant tissues and can be stored for long periods in DNA banks. Curation methods are well developed for other botanical resources such as herbaria, seed banks and botanic gardens, but procedures for the establishment and maintenance of DNA banks have not been well documented. This paper reviews the curation of DNA banks for the characterisation and utilisation of biodiversity and provides guidelines for DNA bank management. It surveys existing DNA banks and outlines their operation. It includes a review of plant DNA collection, preservation, isolation, storage, database management and exchange procedures. We stress that DNA banks require full integration with existing collections such as botanic gardens, herbaria and seed banks, and information retrieval systems that link such facilities, bioinformatic resources and other DNA banks. They also require efficient and well-regulated sample exchange procedures. Only with appropriate curation will maximum utilisation of DNA collections be achieved.

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As part of an ongoing effort to improve the technique of immunoscintigraphy for the detection of human carcinomas with radiolabeled monoclonal antibodies (MABs) to carcinoembryonic antigen (CEA), we have developed a series of MABs to CEA and have studied the effects of low- and physiological molarity buffers on their CEA binding and affinity, as well as their cross-reactivity with granulocyte glycoprotein(s). These in vitro results in different buffer systems were then correlated with the use of these MABs to CEA in the detection of human colon carcinoma grafts in nude mice. Our results show that the binding of CEA by some MABs is influenced by ionic strength and that this may be an important factor in their successful use for the immunolocalization of carcinomas in vivo.

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In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).

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Fungal symbionts commonly occur in plants influencing host growth, physiology, and ecology (Carlile et al., 2001). However, while whole-plant growth responses to biotrophic fungi are readily demonstrated, it has been much more difficult to identify and detect the physiological mechanisms responsible. Previous work on the clonal grass Glyceria striata has revealed that the systemic fungal endophyte Epichloë glyceriae has a positive effect on clonal growth of its host (Pan & Clay, 2002; 2003). The latest study from these authors, in this issue (pp. 467- 475), now suggests that increased carbon movement in hosts infected by E. glyceriae may function as one mechanism by which endophytic fungi could increase plant growth. Given the widespread distribution of both clonal plants and symbiotic fungi, this research will have implications for our understanding of the ecology and evolution of fungus-plant associations in natural communities.

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Aim: We asked whether myocardial flow reserve (MFR) by Rb-82 cardiac PET improve the selection of patients eligible for invasive coronary angiography (ICA). Material and Methods: We enrolled 26 consecutive patients with suspected or known coronary artery disease who performed dynamic Rb-82 PET/CT and (ICA) within 60 days; 4 patients who underwent revascularization or had any cardiovascular events between PET and ICA were excluded. Myocardial blood flow at rest (rMBF), at stress with adenosine (sMBF) and myocardial flow reserve (MFR=sMBF/rMBF) were estimated using the 1-compartment Lortie model (FlowQuant) for each coronary arteries territories. Stenosis severity was assessed using computer-based automated edge detection (QCA). MFR was divided in 3 groups: G1:MFR<1.5, G2:1.5≤MFR<2 and G3:2≤MFR. Stenosis severity was graded as non-significant (<50% or FFR ≥0.8), intermediate (50%≤stenosis<70%) and severe (≥70%). Correlation between MFR and percentage of stenosis were assessed using a non-parametric Spearman test. Results: In G1 (44 vessels), 17 vessels (39%) had a severe stenosis, 11 (25%) an intermediate one, and 16 (36%) no significant stenosis. In G2 (13 vessels), 2 (15%) vessels presented a severe stenosis, 7 (54%) an intermediate one, and 4 (31%) no significant stenosis. In G3 (9 vessels), 0 vessel presented a severe stenosis, 1 (11%) an intermediate one, and 8 (89%) no significant stenosis. Of note, among 11 patients with 3-vessel low MFR<1.5 (G1), 9/11 (82%) had at least one severe stenosis and 2/11 (18%) had at least one intermediate stenosis. There was a significant inverse correlation between stenosis severity and MFR among all 66 territories analyzed (rho= -0.38, p=0.002). Conclusion: Patients with MFR>2 could avoid ICA. Low MFR (G1, G2) on a vessel-based analysis seems to be a poor predictor of severe stenosis severity. Patients with 3-vessel low MFR would benefit from ICA as they are likely to present a significant stenosis in at least one vessel.

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In cooperative multiagent systems, agents interac to solve tasks. Global dynamics of multiagent teams result from local agent interactions, and are complex and difficult to predict. Evolutionary computation has proven a promising approach to the design of such teams. The majority of current studies use teams composed of agents with identical control rules ("geneti- cally homogeneous teams") and select behavior at the team level ("team-level selection"). Here we extend current approaches to include four combinations of genetic team composition and level of selection. We compare the performance of genetically homo- geneous teams evolved with individual-level selection, genetically homogeneous teams evolved with team-level selection, genetically heterogeneous teams evolved with individual-level selection, and genetically heterogeneous teams evolved with team-level selection. We use a simulated foraging task to show that the optimal combination depends on the amount of cooperation required by the task. Accordingly, we distinguish between three types of cooperative tasks and suggest guidelines for the optimal choice of genetic team composition and level of selection