Watershed classification in the Lower Mekong Basin: Rapid economic growth - a source of increasing potential for conflict over resource use

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.

Effect sizes and standardization in neighbourhood models of forest stands: potential biases and misinterpretations

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.

KRAS and HRAS mutations confer resistance to MET targeting in preclinical models of MET-expressing tumor cells.

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.

Development of a Tumour Growth Inhibition Model to Elucidate the Effects of Ritonavir on Intratumoural Metabolism and Anti-tumour Effect of Docetaxel in a Mouse Model for Hereditary Breast Cancer

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.

Wound models for periodontal and bone regeneration: the role of biologic research

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.

Thrombosis during pregnancy: Risks, prevention, and treatment for mother and fetus--harvesting the power of omic technology, biomarkers and in vitro or in vivo models to facilitate the treatment of thrombosis

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.

Decision Support Models for Composing and Navigating through e-Learning Objects

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.

Placental expression of the angiogenic placental growth factor is stimulated by both aldosterone and simulated starvation

Aldosterone is an important factor supporting placental growth and fetal development. Recently, expression of placental growth factor (PlGF) has been observed in response to aldosterone exposure in different models of atherosclerosis. Thus, we hypothesized that aldosterone up-regulates growth-adaptive angiogenesis in pregnancy, via increased placental PlGF expression. We followed normotensive pregnant women (n = 24) throughout pregnancy and confirmed these results in a second independent first trimester cohort (n = 36). Urinary tetrahydroaldosterone was measured by gas chromatography-mass spectrometry and corrected for creatinine. Circulating PlGF concentrations were determined by ELISA. Additionally, cultured cell lines, adrenocortical H295R and choriocarcinoma BeWo cells, as well as primary human third trimester trophoblasts were tested in vitro. PlGF serum concentrations positively correlated with urinary tetrahydroaldosterone corrected for creatinine in these two independent cohorts. This observation was not due to PlGF, which did not induce aldosterone production in cultured H295R cells. On the other hand, PlGF expression was specifically enhanced by aldosterone in the presence of forskolin (p < 0.01) in trophoblasts. A pronounced stimulation of PlGF expression was observed with reduced glucose concentrations simulating starvation (p < 0.001). In conclusion, aldosterone stimulates placental PlGF production, enhancing its availability during human pregnancy, a response amplified by reduced glucose supply. Given the crucial role of PlGF in maintaining a healthy pregnancy, these data support a key role of aldosterone for a healthy pregnancy outcome.

Two distinct filopodia populations at the growth cone allow to sense nanotopographical extracellular matrix cues to guide neurite outgrowth

BACKGROUND The process of neurite outgrowth is the initial step in producing the neuronal processes that wire the brain. Current models about neurite outgrowth have been derived from classic two-dimensional (2D) cell culture systems, which do not recapitulate the topographical cues that are present in the extracellular matrix (ECM) in vivo. Here, we explore how ECM nanotopography influences neurite outgrowth. METHODOLOGY/PRINCIPAL FINDINGS We show that, when the ECM protein laminin is presented on a line pattern with nanometric size features, it leads to orientation of neurite outgrowth along the line pattern. This is also coupled with a robust increase in neurite length. The sensing mechanism that allows neurite orientation occurs through a highly stereotypical growth cone behavior involving two filopodia populations. Non-aligned filopodia on the distal part of the growth cone scan the pattern in a lateral back and forth motion and are highly unstable. Filopodia at the growth cone tip align with the line substrate, are stabilized by an F-actin rich cytoskeleton and enable steady neurite extension. This stabilization event most likely occurs by integration of signals emanating from non-aligned and aligned filopodia which sense different extent of adhesion surface on the line pattern. In contrast, on the 2D substrate only unstable filopodia are observed at the growth cone, leading to frequent neurite collapse events and less efficient outgrowth. CONCLUSIONS/SIGNIFICANCE We propose that a constant crosstalk between both filopodia populations allows stochastic sensing of nanotopographical ECM cues, leading to oriented and steady neurite outgrowth. Our work provides insight in how neuronal growth cones can sense geometric ECM cues. This has not been accessible previously using routine 2D culture systems.

Cell Competition During Growth and Regeneration

Tissue growth and regeneration are autonomous, stem-cell-mediated processes in which stem cells within the organ self-renew and differentiate to create new cells, leading to new tissue. The processes of growth and regeneration require communication and interplay between neighboring cells. In particular, cell competition, which is a process in which viable cells are actively eliminated by more competitive cells, has been increasingly implicated to play an important role. Here, we discuss the existing literature regarding the current landscape of cell competition, including classical pathways and models, fitness fingerprint mechanisms, and immune system mechanisms of cell competition. We further discuss the clinical relevance of cell competition in the physiological processes of tissue growth and regeneration, highlighting studies in clinically important disease models, including oncological, neurological, and cardiovascular diseases.

In Utero Exposure to Antiretroviral Drugs: Effect on Birth Weight and Growth Among HIV-exposed Uninfected Children in Brazil.

BACKGROUND There are concerns about the effects of in utero exposure to antiretroviral drugs (ARVs) on the development of HIV-exposed but uninfected (HEU) children. The aim of this study was to evaluate whether in utero exposure to ARVs is associated with lower birth weight/height and reduced growth during the first 2 years of life. METHODS This cohort study was conducted among HEU infants born between 1996 and 2010 in Tertiary children's hospital in Rio de Janeiro, Brazil. Weight was measured by mechanical scale, and height was measured by measuring board. Z-scores for weight-for-age (WAZ), length-for-age (LAZ) and weight-for-length were calculated. We modeled trajectories by mixed-effects models and adjusted for mother's age, CD4 cell count, viral load, year of birth and family income. RESULTS A total of 588 HEU infants were included of whom 155 (26%) were not exposed to ARVs, 114 (19%) were exposed early (first trimester) and 319 (54%) later. WAZ were lower among infants exposed early compared with infants exposed later: adjusted differences were -0.52 (95% confidence interval [CI]: -0.99 to -0.04, P = 0.02) at birth and -0.22 (95% CI: -0.47 to 0.04, P = 0.10) during follow-up. LAZ were lower during follow-up: -0.35 (95% CI: -0.63 to -0.08, P = 0.01). There were no differences in weight-for-length scores. Z-scores of infants exposed late during pregnancy were similar to unexposed infants. CONCLUSIONS In HEU children, early exposure to ARVs was associated with lower WAZ at birth and lower LAZ up to 2 years of life. Growth of HEU children needs to be monitored closely.

Calibrating a CGE model with NTBs that Incorporates Standard Models of Modern Trade Theory

We propose a way to incorporate NTBs for the four workhorse models of the modern trade literature in computable general equilibrium models (CGEs). CGE models feature intermediate linkages and thus allow us to study global value chains (GVCs). We show that the Ethier-Krugman monopolistic competition model, the Melitz firm heterogeneity model and the Eaton and Kortum model can be defined as an Armington model with generalized marginal costs, generalized trade costs and a demand externality. As already known in the literature in both the Ethier-Krugman model and the Melitz model generalized marginal costs are a function of the amount of factor input bundles. In the Melitz model generalized marginal costs are also a function of the price of the factor input bundles. Lower factor prices raise the number of firms that can enter the market profitably (extensive margin), reducing generalized marginal costs of a representative firm. For the same reason the Melitz model features a demand externality: in a larger market more firms can enter. We implement the different models in a CGE setting with multiple sectors, intermediate linkages, non-homothetic preferences and detailed data on trade costs. We find the largest welfare effects from trade cost reductions in the Melitz model. We also employ the Melitz model to mimic changes in Non tariff Barriers (NTBs) with a fixed cost-character by analysing the effect of changes in fixed trade costs. While we work here with a model calibrated to the GTAP database, the methods developed can also be applied to CGE models based on the WIOD database.