921 resultados para Growth Models (economics)


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BACKGROUND Intrauterine growth restriction (IUGR) occurs in up to 10% of pregnancies and is considered as a major risk to develop various diseases in adulthood, such as cardiovascular diseases, insulin resistance, hypertension or end stage kidney disease. Several IUGR models have been developed in order to understand the biological processes linked to fetal growth retardation, most of them being rat or mouse models and nutritional models. In order to reproduce altered placental flow, surgical models have also been developed, and among them bilateral uterine ligation has been frequently used. Nevertheless, this model has never been developed in the mouse, although murine tools display multiple advantages for biological research. The aim of this work was therefore to develop a mouse model of bilateral uterine ligation as a surgical model of IUGR. RESULTS In this report, we describe the set up and experimental data obtained from three different protocols (P1, P2, P3) of bilateral uterine vessel ligation in the mouse. Ligation was either performed at the cervical end of each uterine horn (P1) or at the central part of each uterine horn (P2 and P3). Time of surgery was E16 (P1), E17 (P2) or E16.5 (P3). Mortality, maternal weight and abortion parameters were recorded, as well as placentas weights, fetal resorption, viability, fetal weight and size. Results showed that P1 in test animals led to IUGR but was also accompanied with high mortality rate of mothers (50%), low viability of fetuses (8%) and high resorption rate (25%). P2 and P3 improved most of these parameters (decreased mortality and improved pregnancy outcomes; improved fetal viability to 90% and 27%, respectively) nevertheless P2 was not associated to IUGR contrary to P3. Thus P3 experimental conditions enable IUGR with better pregnancy and fetuses outcomes parameters that allow its use in experimental studies. CONCLUSIONS Our results show that bilateral uterine artery ligation according to the protocol we have developed and validated can be used as a surgical mouse model of IUGR.

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In the Lower Mekon Basin the extraordinary pace of economic development and growth contradicts with environmental protection. On base of the Watershed Classification Project (WSCP) and the inclusion of a DTM for the entire LMB the potential degradation risk was derived for each land unit. The risks were grouped into five classes, where classes one and two are considered critical with regard to soil erosion when the land is cleared of natural resources. For practical use the database has an enormous potential for further spatial analysis in combination with other datasets, as for example the NCCR North-South uses the WSCP within two research projects.

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Effects of conspecific neighbours on survival and growth of trees have been found to be related to species abundance. Both positive and negative relationships may explain observed abundance patterns. Surprisingly, it is rarely tested whether such relationships could be biased or even spurious due to transforming neighbourhood variables or influences of spatial aggregation, distance decay of neighbour effects and standardization of effect sizes. To investigate potential biases, communities of 20 identical species were simulated with log-series abundances but without species-specific interactions. No relationship of conspecific neighbour effects on survival or growth with species abundance was expected. Survival and growth of individuals was simulated in random and aggregated spatial patterns using no, linear, or squared distance decay of neighbour effects. Regression coefficients of statistical neighbourhood models were unbiased and unrelated to species abundance. However, variation in the number of conspecific neighbours was positively or negatively related to species abundance depending on transformations of neighbourhood variables, spatial pattern and distance decay. Consequently, effect sizes and standardized regression coefficients, often used in model fitting across large numbers of species, were also positively or negatively related to species abundance depending on transformation of neighbourhood variables, spatial pattern and distance decay. Tests using randomized tree positions and identities provide the best benchmarks by which to critically evaluate relationships of effect sizes or standardized regression coefficients with tree species abundance. This will better guard against potential misinterpretations.

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The MET receptor tyrosine kinase is often deregulated in human cancers and several MET inhibitors are evaluated in clinical trials. Similarly to EGFR, MET signals through the RAS-RAF-ERK/MAPK pathway which plays key roles in cell proliferation and survival. Mutations of genes encoding for RAS proteins, particularly in KRAS, are commonly found in various tumors and are associated with constitutive activation of the MAPK pathway. It was shown for EGFR, that KRAS mutations render upstream EGFR inhibition ineffective in EGFR-positive colorectal cancers. Currently, there are no clinical studies evaluating MET inhibition impairment due to RAS mutations. To test the impact of RAS mutations on MET targeting, we generated tumor cells responsive to the MET inhibitor EMD1214063 that express KRAS G12V, G12D, G13D and HRAS G12V variants. We demonstrate that these MAPK-activating RAS mutations differentially interfere with MET-mediated biological effects of MET inhibition. We report increased residual ERK1/2 phosphorylation indicating that the downstream pathway remains active in presence of MET inhibition. Consequently, RAS variants counteracted MET inhibition-induced morphological changes as well as anti-proliferative and anchorage-independent growth effects. The effect of RAS mutants was reversed when MET inhibition was combined with MEK inhibitors AZD6244 and UO126. In an in vivo mouse xenograft model, MET-driven tumors harboring mutated RAS displayed resistance to MET inhibition. Taken together, our results demonstrate for the first time in details the role of KRAS and HRAS mutations in resistance to MET inhibition and suggest targeting both MET and MEK as an effective strategy when both oncogenic drivers are expressed.

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In a mouse tumour model for hereditary breast cancer, we previously explored the anti-cancer effects of docetaxel, ritonavir and the combination of both and studied the effect of ritonavir on the intratumoural concentration of docetaxel. The objective of the current study was to apply pharmacokinetic (PK)-pharmacodynamic (PD) modelling on this previous study to further elucidate and quantify the effects of docetaxel when co-administered with ritonavir. PK models of docetaxel and ritonavir in plasma and in tumour were developed. The effect of ritonavir on docetaxel concentration in the systemic circulation of Cyp3a knock-out mice and in the implanted tumour (with inherent Cyp3a expression) was studied, respectively. Subsequently, we designed a tumour growth inhibition model that included the inhibitory effects of both docetaxel and ritonavir. Ritonavir decreased docetaxel systemic clearance with 8% (relative standard error 0.4%) in the co-treated group compared to that in the docetaxel only-treated group. The docetaxel concentration in tumour tissues was significantly increased by ritonavir with mean area under the concentration-time curve 2.5-fold higher when combined with ritonavir. Observed tumour volume profiles in mice could be properly described by the PK/PD model. In the co-treated group, the enhanced anti-tumour effect was mainly due to increased docetaxel tumour concentration; however, we demonstrated a small but significant anti-tumour effect of ritonavir addition (p value <0.001). In conclusion, we showed that the increased anti-tumour effect observed when docetaxel is combined with ritonavir is mainly caused by enhanced docetaxel tumour concentration and to a minor extent by a direct anti-tumour effect of ritonavir.

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The ultimate goals of periodontal therapy remain the complete regeneration of those periodontal tissues lost to the destructive inflammatory-immune response, or to trauma, with tissues that possess the same structure and function, and the re-establishment of a sustainable health-promoting biofilm from one characterized by dysbiosis. This volume of Periodontology 2000 discusses the multiple facets of a transition from therapeutic empiricism during the late 1960s, toward regenerative therapies, which is founded on a clearer understanding of the biophysiology of normal structure and function. This introductory article provides an overview on the requirements of appropriate in vitro laboratory models (e.g. cell culture), of preclinical (i.e. animal) models and of human studies for periodontal wound and bone repair. Laboratory studies may provide valuable fundamental insights into basic mechanisms involved in wound repair and regeneration but also suffer from a unidimensional and simplistic approach that does not account for the complexities of the in vivo situation, in which multiple cell types and interactions all contribute to definitive outcomes. Therefore, such laboratory studies require validatory research, employing preclinical models specifically designed to demonstrate proof-of-concept efficacy, preliminary safety and adaptation to human disease scenarios. Small animal models provide the most economic and logistically feasible preliminary approaches but the outcomes do not necessarily translate to larger animal or human models. The advantages and limitations of all periodontal-regeneration models need to be carefully considered when planning investigations to ensure that the optimal design is adopted to answer the specific research question posed. Future challenges lie in the areas of stem cell research, scaffold designs, cell delivery and choice of growth factors, along with research to ensure appropriate gingival coverage in order to prevent gingival recession during the healing phase.

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Maternal thromboembolism and a spectrum of placenta-mediated complications including the pre-eclampsia syndromes, fetal growth restriction, fetal loss, and abruption manifest a shared etiopathogenesis and predisposing risk factors. Furthermore, these maternal and fetal complications are often linked to subsequent maternal health consequences that comprise the metabolic syndrome, namely, thromboembolism, chronic hypertension, and type II diabetes. Traditionally, several lines of evidence have linked vasoconstriction, excessive thrombosis and inflammation, and impaired trophoblast invasion at the uteroplacental interface as hallmark features of the placental complications. "Omic" technologies and biomarker development have been largely based upon advances in vascular biology, improved understanding of the molecular basis and biochemical pathways responsible for the clinically relevant diseases, and increasingly robust large cohort and/or registry based studies. Advances in understanding of innate and adaptive immunity appear to play an important role in several pregnancy complications. Strategies aimed at improving prediction of these pregnancy complications are often incorporating hemodynamic blood flow data using non-invasive imaging technologies of the utero-placental and maternal circulations early in pregnancy. Some evidence suggests that a multiple marker approach will yield the best performing prediction tools, which may then in turn offer the possibility of early intervention to prevent or ameliorate these pregnancy complications. Prediction of maternal cardiovascular and non-cardiovascular consequences following pregnancy represents an important area of future research, which may have significant public health consequences not only for cardiovascular disease, but also for a variety of other disorders, such as autoimmune and neurodegenerative diseases.

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Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed. Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative. Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects. The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.