HNF1α and CDX2 transcriptional factors bind to cadherin-17 (CDH17) gene promoter and modulate its expression in hepatocellular carcinoma

Cadherin-17 (CDH17) belongs to the cell adhesion cadherin family with a prominent role in tumorigenesis. It is highly expressed in human hepatocellular carcinoma (HCC) and is proposed to be a biomarker and therapeutic molecule for liver malignancy. The present study aims to identify the transcription factors which interact and regulate CDH17 promoter activity that might contribute to the up-regulation of CDH17 gene in human HCC. A 1-kb upstream sequence of CDH17 gene was cloned and the promoter activity was studied by luciferase reporter assay. By bioinformatics analysis, deletion and mutation assays, and chromatin immunoprecipitation studies, we identified hepatic nuclear factor 1a (HNF1a) and caudal-related homeobox 2 (CDX2) binding sites at the proximal promoter region which modulate the CDH17 promoter activities in two HCC cell lines (Hep3B and MHCC97L). A consistent down-regulation of CDH17 and the two transcriptional activators (HNF1a and CDX2) expression was found in the liver of mouse during development, as well as in human liver cancer cells with less metastatic potential. Suppression of HNF1a and CDX2 expression by small interfering RNA (siRNA) significantly down-regulated expressions of CDH17 and its downstream target cyclin D1 and the viability of HCC cells in vitro. In summary, we identified the minimal promoter region of CDH17 that is regulated by HNF1a and CDX2 transcriptional factors. The present findings enhance our understanding on the regulatory mechanisms of CDH17 oncogene in HCC, and may shed new insights into targeting CDH17 expression as potential therapeutic intervention for cancer treatment. © 2010 Wiley-Liss, Inc.preprin

A laboratory characterisation of inorganic iodine emissions from the sea surface: dependence on oceanic variables and parameterisation for global modelling

Reactive iodine compounds play a significant role in the atmospheric chemistry of the oceanic boundary layer by influencing the oxidising capacity through catalytically removing O3 and altering the HOx and NOx balance. The sea-to-air flux of iodine over the open ocean is therefore an important quantity in assessing these impacts on a global scale. This paper examines the effect of a number of relevant environmental parameters, including water temperature, salinity and organic compounds, on the magnitude of the HOI and I2 fluxes produced from the uptake of O3 and its reaction with iodide ions in aqueous solution. The results of these laboratory experiments and those reported previously (Carpenter et al., 2013), along with sea surface iodide concentrations measured or inferred from measurements of dissolved total iodine and iodate reported in the literature, were then used to produce parameterised expressions for the HOI and I2 fluxes as a function of wind speed, sea-surface temperature and O3. These expressions were used in the Tropospheric HAlogen chemistry MOdel (THAMO) to compare with MAX-DOAS measurements of iodine monoxide (IO) performed during the HaloCAST-P cruise in the eastern Pacific ocean (Mahajan et al., 2012). The modelled IO agrees reasonably with the field observations, although significant discrepancies are found during a period of low wind speeds (< 3 m s&minus;1), when the model overpredicts IO by up to a factor of 3. The inorganic iodine flux contributions to IO are found to be comparable to, or even greater than, the contribution of organo-iodine compounds and therefore its inclusion in atmospheric models is important to improve predictions of the influence of halogen chemistry in the marine boundary layer

Null Models of Economic Networks: The Case of the World Trade Web

In all empirical-network studies, the observed properties of economic networks are informative only if compared with a well-defined null model that can quantitatively predict the behavior of such properties in constrained graphs. However, predictions of the available null-model methods can be derived analytically only under assumptions (e.g., sparseness of the network) that are unrealistic for most economic networks like the World Trade Web (WTW). In this paper we study the evolution of the WTW using a recently-proposed family of null network models. The method allows to analytically obtain the expected value of any network statistic across the ensemble of networks that preserve on average some local properties, and are otherwise fully random. We compare expected and observed properties of the WTW in the period 1950-2000, when either the expected number of trade partners or total country trade is kept fixed and equal to observed quantities. We show that, in the binary WTW, node-degree sequences are sufficient to explain higher-order network properties such as disassortativity and clustering-degree correlation, especially in the last part of the sample. Conversely, in the weighted WTW, the observed sequence of total country imports and exports are not sufficient to predict higher-order patterns of the WTW. We discuss some important implications of these findings for international-trade models.Comment: 39 pages, 46 figures, 2 table

Radar Detectability Studies of Slow and Small Zodiacal Dust Cloud Particles. III. The Role of Sodium and the Head Echo Size on the Probability of Detection

We present a path forward on a long-standing issue concerning the flux of small and slow meteoroids, which are believed to be the dominant portion of the incoming meteoric mass flux into the Earth's atmosphere. Such a flux, which is predicted by dynamical dust models of the Zodiacal Cloud, is not evident in ground-based radar observations. For decades this was attributed to the fact that the radars used for meteor observations lack the sensitivity to detect this population, due to the small amount of ionization produced by slow-velocity meteors. Such a hypothesis has been challenged by the introduction of meteor head echo (HE) observations with High Power and Large Aperture radars, in particular the Arecibo 430 MHz radar. Janches et al. developed a probabilistic approach to estimate the detectability of meteors by these radars and initially showed that, with the current knowledge of ablation and ionization, such particles should dominate the detected rates by one to two orders of magnitude compared to the actual observations. In this paper, we include results in our model from recently published laboratory measurements, which showed that (1) the ablation of Na is less intense covering a wider altitude range; and (2) the ionization probability, βip for Na atoms in the air is up to two orders of magnitude smaller for low speeds than originally believed. By applying these results and using a somewhat smaller size of the HE radar target we offer a solution that reconciles these observations with model predictions

The chemistry of protoplanetary fragments formed via gravitational instabilities

In this paper, we model the chemical evolution of a 0.25 M$_{\odot}$ protoplanetary disc surrounding a 1 M$_{\odot}$ star that undergoes fragmentation due to self-gravity. We use Smoothed Particle Hydrodynamics including a radiative transfer scheme, along with time-dependent chemical evolution code to follow the composition of the disc and resulting fragments over approximately 4000 yrs. Initially, four quasi-stable fragments are formed, of which two are eventually disrupted by tidal torques in the disc. From the results of our chemical modelling, we identify species that are abundant in the fragments (e.g. H$_{\rm 2}$O, H$_{\rm 2}$S, HNO, N$_{\rm 2}$, NH$_{\rm 3}$, OCS, SO), species that are abundant in the spiral shocks within the disc (e.g. CO, CH$_{\rm 4}$, CN, CS, H$_{\rm 2}$CO), and species which are abundant in the circumfragmentary material (e.g. HCO$^{\rm +}$). Our models suggest that in some fragments it is plausible for grains to sediment to the core before releasing their volatiles into the planetary envelope, leading to changes in, e.g., the C/O ratio of the gas and ice components. We would therefore predict that the atmospheric composition of planets generated by gravitational instability should not necessarily follow the bulk chemical composition of the local disc material

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%

The filtering equations revisited

The problem of nonlinear filtering has engendered a surprising number of mathematical techniques for its treatment. A notable example is the change-of--probability-measure method originally introduced by Kallianpur and Striebel to derive the filtering equations and the Bayes-like formula that bears their names. More recent work, however, has generally preferred other methods. In this paper, we reconsider the change-of-measure approach to the derivation of the filtering equations and show that many of the technical conditions present in previous work can be relaxed. The filtering equations are established for general Markov signal processes that can be described by a martingale-problem formulation. Two specific applications are treated

The International-Trade Network: Gravity Equations and Topological Properties

This paper begins to explore the determinants of the topological properties of the international - trade network (ITN). We fit bilateral-trade flows using a standard gravity equation to build a "residual" ITN where trade-link weights are depurated from geographical distance, size, border effects, trade agreements, and so on. We then compare the topological properties of the original and residual ITNs. We find that the residual ITN displays, unlike the original one, marked signatures of a complex system, and is characterized by a very different topological architecture. Whereas the original ITN is geographically clustered and organized around a few large-sized hubs, the residual ITN displays many small-sized but trade-oriented countries that, independently of their geographical position, either play the role of local hubs or attract large and rich countries in relatively complex trade-interaction patterns

Markedly Divergent Tree Assemblage Responses to Tropical Forest Loss and Fragmentation across a Strong Seasonality Gradient

We examine the effects of forest fragmentation on the structure and composition of tree assemblages within three seasonal and aseasonal forest types of southern Brazil, including evergreen, Araucaria, and deciduous forests. We sampled three southernmost Atlantic Forest landscapes, including the largest continuous forest protected areas within each forest type. Tree assemblages in each forest type were sampled within 10 plots of 0.1 ha in both continuous forests and 10 adjacent forest fragments. All trees within each plot were assigned to trait categories describing their regeneration strategy, vertical stratification, seed-dispersal mode, seed size, and wood density. We detected differences among both forest types and landscape contexts in terms of overall tree species richness, and the density and species richness of different functional groups in terms of regeneration strategy, seed dispersal mode and woody density. Overall, evergreen forest fragments exhibited the largest deviations from continuous forest plots in assemblage structure. Evergreen, Araucaria and deciduous forests diverge in the functional composition of tree floras, particularly in relation to regeneration strategy and stress tolerance. By supporting a more diversified light-demanding and stress-tolerant flora with reduced richness and abundance of shade-tolerant, old-growth species, both deciduous and Araucaria forest tree assemblages are more intrinsically resilient to contemporary human-disturbances, including fragmentation-induced edge effects, in terms of species erosion and functional shifts. We suggest that these intrinsic differences in the direction and magnitude of responses to changes in landscape structure between forest types should guide a wide range of conservation strategies in restoring fragmented tropical forest landscapes worldwide

An algorithm for satellite-based burned area mapping using change point detection and Markov random fields

Area burned in tropical savannas of Brazil and Australia was mapped using SPOT-VGT daily 1km resolution imagery and a new algorithm based on change point detection techniques. Each study area covers about 250,000 km2 and the mapping exercise spans a 11-yr period (1999-2009). Our algorithm addresses each pixel as a time series and detects changes in the statistical properties (mean and variance) of NIR and SWIR reflectance values, toidentify potential burning dates. We compare the performance of binary segmentation (BinSeg) and Pruned Exact Linear Time (PELT) change point detection techniques. Mean reflectance values observed at a pixel over the week after a change point has been detected are compared with a biome-specific statistical distribution of burned area reflectance values, to assess the probability that the change point detected does correspond to a burn event. Change points corresponding to an increase in reflectance are dismissed as potential burn events, as are those occurring outside of a pre-defined fire season. In the last step of the algorithm, monthly burned area probability maps are converted to dichotomous (burned-unburned maps), using Markov Random Fields. A preliminary assessment of our results is performed by comparing them with those from the MODIS active fires and burned area products, taking into account differences in spatial resolution between the two sensors