Cabo Verde, "Pousada" nos Caminhos do Atlântico. Interinluências culturais num arquipélago miscigenado

[POR] Descoberto entre 1460 e 1462, o Arquipélago de Cabo Verde, situado no Oceano Atlântico, constituiu ao longo de vários séculos, escala obrigatória dos navios que faziam as ligações atlânticas entre os portos das Américas, da Europa e da África Graças a sua situação privilegiada, o espaço cabo-verdiano não foi um mero ponto de reabastecimento, mas também um importante ponto de cruzamento de culturas e de raças. Pretende-se, neste texto, abordar o papel que Cabo Verde teve no Atlântico incidindo, particularmente, na dimensão cultural resultante do contacto entre povos e culturas provenientes de diferentes paragens que se fixaram no arquipélago ou que por aqui passaram. Procurar-se-á evidenciar não só a importância que Cabo Verde teve enquanto ponto de passagem obrigatória mas, sobretudo, as contribuições que mais marcadamente se denunciaram, isto é, os apports culturais que mais se acentuaram em Cabo Verde, como processos recebidos dos estrangeiros que por estas ilhas se cruzaram.

Lokalisierung der Fortsatz-induzierenden Domäne von Transmembran-Agrin

Aggregation oder Überexpression der Transmembran-Isoform des extrazellulären Matrix-Proteoglycans Agrin in Neuronen führt zur Bildung zahlreicher filopodienartiger Fortsätze auf Axonen und Dendriten. Ähnliche Fortsätze können auch durch Überexpression von Transmembran-Agrin in verschiedenen nicht-neuronalen Zelllinien induziert werden. Untersuchungen zu dieser Fortsatz-induzierenden Aktivität in Neuronen und nicht-neuronalen Zellen zeigen, dass der extrazelluläre Teil von Transmembran-Agrin für die Fortsatzbildung notwendig ist. In dieser Arbeit wurde mittels verschiedener Deletions- und Mutationskonstrukte der Bereich zwischen den Cysteinen C535 und C567 der siebten Follistatin-ähnlichen Domäne von Transmembran-Agrin als essentiell für die Bildung der filopodienartigen Fortsätze identifiziert. Die siebte Follistatin-ähnliche Domäne konnte durch die erste oder sechste, jedoch nicht durch die achte Follistatin-ähnliche Domäne funktionell ersetzt werden, was für eine funktionelle Redundanz bei einigen Follistatin-ähnlichen Domänen Agrins spricht. Zudem scheint eine kritische Distanz der siebten Follistatin-ähnlichen Domäne zur Plasmamembran für die Fortsatzbildung wichtig zu sein. Diese Ergebnisse zeigen, dass unterschiedliche Regionen innerhalb Agrins für die Bildung der Synapse an der neuromuskulären Endplatte und der Fortsätze im Zentralnervensystem verantwortlich sind, und deuten auf eine Funktion der Follistatin-ähnlichen Domänen Agrins bei der Entwicklung des Zentralnervensystems hin.

Listeria monocytogenes spreads within the brain by actin-based intra-axonal migration

Listeria monocytogenes rhombencephalitis is a severe progressive disease despite a swift intrathecal immune response. Based on previous observations, we hypothesized that the disease progresses by intra-axonal spread within the central nervous system. To test this hypothesis, neuroanatomical mapping of lesions, immunofluorescence analysis, and electron microscopy were performed on brains of ruminants with naturally occurring rhombencephalitis. In addition, infection assays were performed in bovine brain cell cultures. Mapping of lesions revealed a consistent pattern with a preferential affection of certain nuclear areas and white matter tracts, indicating that Listeria monocytogenes spreads intra-axonally within the brain along interneuronal connections. These results were supported by immunofluorescence and ultrastructural data localizing Listeria monocytogenes inside axons and dendrites associated with networks of fibrillary structures consistent with actin tails. In vitro infection assays confirmed that bacteria were moving within axon-like processes by employing their actin tail machinery. Remarkably, in vivo, neutrophils invaded the axonal space and the axon itself, apparently by moving between split myelin lamellae of intact myelin sheaths. This intra-axonal invasion of neutrophils was associated with various stages of axonal degeneration and bacterial phagocytosis. Paradoxically, the ensuing adaxonal microabscesses appeared to provide new bacterial replication sites, thus supporting further bacterial spread. In conclusion, intra-axonal bacterial migration and possibly also the innate immune response play an important role in the intracerebral spread of the agent and hence the progression of listeric rhombencephalitis.

Regional surface morphology of comet 67P/Churyumov-Gerasimenko from Rosetta/OSIRIS images

Aims. The OSIRIS camera onboard the Rosetta spacecraft has been acquiring images of the comet 67P/Churyumov-Gerasimenko (67P)'s nucleus at spatial resolutions down to similar to 0.17 m/px ever since Aug. 2014. These images have yielded unprecedented insight into the morphological diversity of the comet's surface. This paper presents an overview of the regional morphology of comet 67P. Methods. We used the images that were acquired at orbits similar to 20-30 km from the center of the comet to distinguish different regions on the surface and introduce the basic regional nomenclature adopted by all papers in this Rosetta special feature that address the comet's morphology and surface processes. We used anaglyphs to detect subtle regional and topographical boundaries and images from close orbit (similar to 10 km from the comet's center) to investigate the fine texture of the surface. Results. Nineteen regions have currently been defined on the nucleus based on morphological and/or structural boundaries, and they can be grouped into distinctive region types. Consolidated, fractured regions are the most common region type. Some of these regions enclose smooth units that appear to settle in gravitational sinks or topographically low areas. Both comet lobes have a significant portion of their surface covered by a dusty coating that appears to be recently placed and shows signs of mobilization by aeolian-like processes. The dusty coatings cover most of the regions on the surface but are notably absent from a couple of irregular large depressions that show sharp contacts with their surroundings and talus-like deposits in their interiors, which suggests that short-term explosive activity may play a significant role in shaping the comet's surface in addition to long-term sublimation loss. Finally, the presence of layered brittle units showing signs of mechanical failure predominantly in one of the comet's lobes can indicate a compositional heterogeneity between the two lobes.

A formalism and method for representing and reasoning with process models authored by subject matter experts

Enabling Subject Matter Experts (SMEs) to formulate knowledge without the intervention of Knowledge Engineers (KEs) requires providing SMEs with methods and tools that abstract the underlying knowledge representation and allow them to focus on modeling activities. Bridging the gap between SME-authored models and their representation is challenging, especially in the case of complex knowledge types like processes, where aspects like frame management, data, and control flow need to be addressed. In this paper, we describe how SME-authored process models can be provided with an operational semantics and grounded in a knowledge representation language like F-logic in order to support process-related reasoning. The main results of this work include a formalism for process representation and a mechanism for automatically translating process diagrams into executable code following such formalism. From all the process models authored by SMEs during evaluation 82% were well-formed, all of which executed correctly. Additionally, the two optimizations applied to the code generation mechanism produced a performance improvement at reasoning time of 25% and 30% with respect to the base case, respectively.

Type 1 nitrergic (ND1) cells of the rabbit retina: Comparison with other axon-bearing amacrine cells

NADPH diaphorase (NADPHd) histochemistry labels two types of nitrergic amacrine cells in the rabbit retina. Both the large ND1 cells and the small ND2 cells stratify in the middle of the inner plexiform layer, and their overlapping processes produce a dense plexus, which makes it difficult to trace the morphology of single cells. The complete morphology of the ND1 amacrine cells has been revealed by injecting Neurobiotin into large round somata in the inner nuclear layer, which resulted in the labelling of amacrine cells whose proximal morphology and stratification matched those of the ND1 cells stained by NADPHd histochemistry. The Neurobiotin-injected ND1 cells showed strong homologous tracer coupling to surrounding ND1 cells, and double-labelling experiments confirmed that these coupled cells showed NADPHd reactivity. The ND1 amacrine cells branch in stratum 3 of the inner plexiform layer, where they produce a sparsely branched dendritic tree of 400-600 mum diameter in ventral peripheral retina. In addition, each cell gives rise to several fine beaded processes, which arise either from a side branch of the dendritic tree or from the tapering of a distal dendrite. These axon-like processes branch successively within the vicinity of the dendritic field before extending, with little or no further branching, for 3-5 mm from the soma in ventral peripheral retina. Consequently, these cells may span one-third of the visual field of each eye, and their spatial extent appears to be greater than that of most other types of axon-bearing amacrine cells injected with Neurobiotin in this study. The morphology and tracer-coupling pattern of the ND1 cells are compared with those of confirmed type 1 catecholaminergic cells, a presumptive type 2 catecholaminergic cell, the type 1 polyaxonal. cells, the long-range amacrine cells, a novel type of axon-bearing cell that also branches in stratum 3, and a type of displaced amacrine cell that may correspond to the type 2 polyaxonal cell. (C) 2004 Wiley-Liss, Inc.

The type 1 polyaxonal amacrine cells of the rabbit retina: A tracer-coupling study

The type 1 polyaxonal (PA1) cell is a distinct type of axon-bearing amacrine cell whose soma commonly occupies an interstitial position in the inner plexiform layer; the proximal branches of the sparse dendritic tree produce 1-4 axon-like processes, which form an extensive axonal arbor that is concentric with the smaller dendritic tree (Dacey, 1989; Famiglietti, 1992a,b). In this study, intracellular injections of Neurobiotin have revealed the complete dendritic and axonal morphology of the PA1 cells in the rabbit retina, as well as labeling the local array of PA1 cells through homologous tracer coupling. The dendritic-field area of the PA1 cells increased from a minimum of 0.15 mm(2) (0.44-mm equivalent diameter) on the visual streak to a maximum of 0.67 mm(2) (0.92-mm diameter) in the far periphery; the axonal-field area also showed a 3-fold variation across the retina, ranging from 3.1 mm(2) (2.0-mm diameter) to 10.2 mm(2) (3.6-mm diameter). The increase in dendritic- and axonal-field size was accompanied by a reduction in cell density, from 60 cells/mm(2) in the visual streak to 20 cells/mm(2) in the far periphery, so that the PA1 cells showed a 12 times overlap of their dendritic fields across the retina and a 200-300 times overlap of their axonal fields. Consequently, the axonal plexus was much denser than the dendritic plexus, with each square millimeter of retina containing similar to100 mm of dendrites and similar to1000 mm of axonal processes. The strong homologous tracer coupling revealed that similar to45% of the PA1 somata were located in the inner nuclear layer, similar to50% in the inner plexiform layer, and similar to5% in the ganglion cell layer. In addition, the Neurobiotin-injected PA1 cells sometimes showed clear heterologous tracer coupling to a regular array of small ganglion cells, which were present at half the density of the PA1 cells. The PA1 cells were also shown to contain elevated levels of gamma-aminobutyric acid (GABA), like other axon-bearing amacrine cells.

BRACHYURY confers cancer stem cell characteristics on colorectal cancer cells

Cancer stem cells (CSCs) are initiating cells in colorectal cancer (CRC). Colorectal tumours undergo epithelial to mesenchymal transition (EMT)-like processes at the invasive front, enabling invasion and metastasis, and recent studies have linked this process to the acquisition of stem cell-like properties. It is of fundamental importance to understand the molecular events leading to the establishment of cancer initiating cells and how these mechanisms relate to cellular transitions during tumourigenesis. We use an in vitro system to recapitulate changes in CRC cells at the invasive front (mesenchymal-like cells) and central mass (epithelial-like cells) of tumours. We show that the mesoderm inducer BRACHYURY is expressed in a subpopulation of CRC cells that resemble invasive front mesenchymal-like cells, where it acts to impose characteristics of CSCs in a fully reversible manner, suggesting reversible formation and modulation of such cells. BRACHYURY, itself regulated by the oncogene β-catenin, influences NANOG and other 'stemness' markers including a panel of markers defining CRC-CSC whose presence has been linked to poor patient prognosis. Similar regulation of NANOG through BRACHYURY was observed in other cells lines, suggesting this might be a pathway common to cancer cells undergoing mesenchymal transition. We suggest that BRACHYURY may regulate NANOG in mesenchymal-like CRC cells to impose a 'plastic-state', allowing competence of cells to respond to signals prompting invasion or metastasis. Copyright © 2011 UICC.

Bayesian Inference in Large-scale Problems

Many modern applications fall into the category of "large-scale" statistical problems, in which both the number of observations n and the number of features or parameters p may be large. Many existing methods focus on point estimation, despite the continued relevance of uncertainty quantification in the sciences, where the number of parameters to estimate often exceeds the sample size, despite huge increases in the value of n typically seen in many fields. Thus, the tendency in some areas of industry to dispense with traditional statistical analysis on the basis that "n=all" is of little relevance outside of certain narrow applications. The main result of the Big Data revolution in most fields has instead been to make computation much harder without reducing the importance of uncertainty quantification. Bayesian methods excel at uncertainty quantification, but often scale poorly relative to alternatives. This conflict between the statistical advantages of Bayesian procedures and their substantial computational disadvantages is perhaps the greatest challenge facing modern Bayesian statistics, and is the primary motivation for the work presented here.

Two general strategies for scaling Bayesian inference are considered. The first is the development of methods that lend themselves to faster computation, and the second is design and characterization of computational algorithms that scale better in n or p. In the first instance, the focus is on joint inference outside of the standard problem of multivariate continuous data that has been a major focus of previous theoretical work in this area. In the second area, we pursue strategies for improving the speed of Markov chain Monte Carlo algorithms, and characterizing their performance in large-scale settings. Throughout, the focus is on rigorous theoretical evaluation combined with empirical demonstrations of performance and concordance with the theory.

One topic we consider is modeling the joint distribution of multivariate categorical data, often summarized in a contingency table. Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. In Chapter 2, we derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions.

Latent class models for the joint distribution of multivariate categorical, such as the PARAFAC decomposition, data play an important role in the analysis of population structure. In this context, the number of latent classes is interpreted as the number of genetically distinct subpopulations of an organism, an important factor in the analysis of evolutionary processes and conservation status. Existing methods focus on point estimates of the number of subpopulations, and lack robust uncertainty quantification. Moreover, whether the number of latent classes in these models is even an identified parameter is an open question. In Chapter 3, we show that when the model is properly specified, the correct number of subpopulations can be recovered almost surely. We then propose an alternative method for estimating the number of latent subpopulations that provides good quantification of uncertainty, and provide a simple procedure for verifying that the proposed method is consistent for the number of subpopulations. The performance of the model in estimating the number of subpopulations and other common population structure inference problems is assessed in simulations and a real data application.

In contingency table analysis, sparse data is frequently encountered for even modest numbers of variables, resulting in non-existence of maximum likelihood estimates. A common solution is to obtain regularized estimates of the parameters of a log-linear model. Bayesian methods provide a coherent approach to regularization, but are often computationally intensive. Conjugate priors ease computational demands, but the conjugate Diaconis--Ylvisaker priors for the parameters of log-linear models do not give rise to closed form credible regions, complicating posterior inference. In Chapter 4 we derive the optimal Gaussian approximation to the posterior for log-linear models with Diaconis--Ylvisaker priors, and provide convergence rate and finite-sample bounds for the Kullback-Leibler divergence between the exact posterior and the optimal Gaussian approximation. We demonstrate empirically in simulations and a real data application that the approximation is highly accurate, even in relatively small samples. The proposed approximation provides a computationally scalable and principled approach to regularized estimation and approximate Bayesian inference for log-linear models.

Another challenging and somewhat non-standard joint modeling problem is inference on tail dependence in stochastic processes. In applications where extreme dependence is of interest, data are almost always time-indexed. Existing methods for inference and modeling in this setting often cluster extreme events or choose window sizes with the goal of preserving temporal information. In Chapter 5, we propose an alternative paradigm for inference on tail dependence in stochastic processes with arbitrary temporal dependence structure in the extremes, based on the idea that the information on strength of tail dependence and the temporal structure in this dependence are both encoded in waiting times between exceedances of high thresholds. We construct a class of time-indexed stochastic processes with tail dependence obtained by endowing the support points in de Haan's spectral representation of max-stable processes with velocities and lifetimes. We extend Smith's model to these max-stable velocity processes and obtain the distribution of waiting times between extreme events at multiple locations. Motivated by this result, a new definition of tail dependence is proposed that is a function of the distribution of waiting times between threshold exceedances, and an inferential framework is constructed for estimating the strength of extremal dependence and quantifying uncertainty in this paradigm. The method is applied to climatological, financial, and electrophysiology data.

The remainder of this thesis focuses on posterior computation by Markov chain Monte Carlo. The Markov Chain Monte Carlo method is the dominant paradigm for posterior computation in Bayesian analysis. It has long been common to control computation time by making approximations to the Markov transition kernel. Comparatively little attention has been paid to convergence and estimation error in these approximating Markov Chains. In Chapter 6, we propose a framework for assessing when to use approximations in MCMC algorithms, and how much error in the transition kernel should be tolerated to obtain optimal estimation performance with respect to a specified loss function and computational budget. The results require only ergodicity of the exact kernel and control of the kernel approximation accuracy. The theoretical framework is applied to approximations based on random subsets of data, low-rank approximations of Gaussian processes, and a novel approximating Markov chain for discrete mixture models.

Data augmentation Gibbs samplers are arguably the most popular class of algorithm for approximately sampling from the posterior distribution for the parameters of generalized linear models. The truncated Normal and Polya-Gamma data augmentation samplers are standard examples for probit and logit links, respectively. Motivated by an important problem in quantitative advertising, in Chapter 7 we consider the application of these algorithms to modeling rare events. We show that when the sample size is large but the observed number of successes is small, these data augmentation samplers mix very slowly, with a spectral gap that converges to zero at a rate at least proportional to the reciprocal of the square root of the sample size up to a log factor. In simulation studies, moderate sample sizes result in high autocorrelations and small effective sample sizes. Similar empirical results are observed for related data augmentation samplers for multinomial logit and probit models. When applied to a real quantitative advertising dataset, the data augmentation samplers mix very poorly. Conversely, Hamiltonian Monte Carlo and a type of independence chain Metropolis algorithm show good mixing on the same dataset.

Quantification of magmatic and hydrothermal processes in a peralkaline syenite-alkali granite complex based on textures, phase equilibria, and stable and radiogenic isotopes

The Puklen complex of the Mid-Proterozoic Gardar Province, South Greenland, consists of various silica-saturated to quartz-bearing syenites, which are intruded by a peralkaline granite. The primary mafic minerals in the syenites are augite +/- olivine + Fe-Ti oxide + amphibole. Ternary feldspar thermometry and phase equilibria among mafic silicates yield T = 950-750degreesC, a(SiO2) = 0.7-1 and an f(O2) of 1-3 log units below the fayalite-magnetite-quartz (FMQ) buffer at 1 kbar. In the granites, the primary mafic minerals are ilmenite and Li-bearing arfvedsonite, which crystallized at temperatures below 750degreesC and at f(O2) values around the FMQ buffer. In both rock types, a secondary post-magmatic assemblage overprints the primary magmatic phases. In syenites, primary Ca-bearing minerals are replaced by Na-rich minerals such as aegirine-augite and albite, resulting in the release of Ca. Accordingly, secondary minerals include ferro-actinolite, (calcite-siderite)(ss), titanite and andradite in equilibrium with the Na-rich minerals. Phase equilibria indicate that formation of these minerals took place over a long temperature interval from near-magmatic temperatures down to similar to300degreesC. In the course of this cooling, oxygen fugacity rose in most samples. For example, late-stage aegirine in granites formed at the expense of arfvedsonite at temperatures below 300degreesC and at an oxygen fugacity above the haematite-magnetite (HM) buffer. The calculated delta(18)O(melt) value for the syenites (+5.9 to +6.3parts per thousand) implies a mantle origin, whereas the inferred delta(18)O(melt) value of <+5.1parts per thousand for the granitic melts is significantly lower. Thus, the granites require an additional low-delta(18)O contaminant, which was not involved in the genesis of the syenites. Rb/Sr data for minerals of both rock types indicate open-system behaviour for Rb and Sr during post-magmatic metasomatism. Neodymium isotope compositions (epsilonNd(1170 Ma) = -3.8 to -6.4) of primary minerals in syenites are highly variable, and suggest that assimilation of crustal rocks occurred to variable extents. Homogeneous epsilon(Nd) values of -5.9 and -6.0 for magmatic amphibole in the granites lie within the range of the syenites. Because of the very similar neodymium isotopic compositions of magmatic and late- to post-magmatic minerals from the same syenite samples a principally closed-system behaviour during cooling is implied. In contrast, for the granites an externally derived fluid phase is required to explain the extremely low epsilon(Nd) values of about -10 and low delta(18)O between +2.0 and +0.5parts per thousand for late-stage aegirine, indicating an open system in the late-stage history. In this study we show that the combination of phase equilibria constraints with stable and radiogenic isotope data on mineral separates can provide much better constraints on magma evolution during emplacement and crystallization than conventional whole-rock studies.

Stable isotope (C, O, S) systematics of the mercury mineralization at Idrija, Slovenia: constraints on fluid source and alteration processes

The world-class Idrija mercury deposit (western Slovenia) is hosted by highly deformed Permocarboniferous to Middle Triassic sedimentary rocks within a complex tectonic structure at the transition between the External Dinarides and the Southern Alps. Concordant and discordant mineralization formed concomitant with Middle Triassic bimodal volcanism in an aborted rift. A multiple isotopic (C, O, S) investigation of host rocks and ore minerals was performed to put constraints on the source and composition of the fluid, and the hydrothermal alteration. The distributions of the delta(13)C and delta(18)O values of host and gangue carbonates are indicative of a fracture-controlled hydrothermal system, with locally high fluid-rock ratios. Quantitative modeling of the delta(13)C and delta(18)O covariation for host carbonates during temperature dependent fluid-rock interaction, and concomitant precipitation of void-filling dolomites points to a slightly acidic hydrothermal fluid (delta(13)Capproximate to-4parts per thousand and delta(18)Oapproximate to+10parts per thousand), which most likely evolved during isotopic exchange with carbonates under low fluid/rock ratios. The delta(34)S values of hydrothermal and sedimentary sulfur minerals were used to re-evaluate the previously proposed magmatic and evaporitic sulfur sources for the mineralization, and to assess the importance of other possible sulfur sources such as the contemporaneous seawater sulfate, sedimentary pyrite, and organic sulfur compounds. The delta(34)S values of the sulfides show a large variation at deposit down to hand-specimen scale. They range for cinnabar and pyrite from -19.1 to +22.8parts per thousand, and from -22.4 to +59.6parts per thousand, respectively, suggesting mixing of sulfur from different sources. The peak of delta(34)S values of cinnabar and pyrite close to 0parts per thousand is compatible with ore sulfur derived dominantly from a magmatic fluid and/or from hydrothermal leaching of basement rocks. The similar stratigraphic trends of the delta(34)S values of both cinnabar and pyrite suggest a minor contribution of sedimentary sulfur (pyrite and organic sulfur) to the ore formation. Some of the positive delta(34)S values are probably derived from thermochemical reduction of evaporitic and contemporaneous seawater sulfates.

Impaired aldehyde dehydrogenase 1 subfamily member 2A-dependent retinoic acid signaling is related with a mesenchymal-like phenotype and an unfavorable prognosis of head and neck squamous cell carcinoma.

BACKGROUND: An inverse correlation between expression of the aldehyde dehydrogenase 1 subfamily A2 (ALDH1A2) and gene promoter methylation has been identified as a common feature of oropharyngeal squamous cell carcinoma (OPSCC). Moreover, low ALDH1A2 expression was associated with an unfavorable prognosis of OPSCC patients, however the causal link between reduced ALDH1A2 function and treatment failure has not been addressed so far. METHODS: Serial sections from tissue microarrays of patients with primary OPSCC (n = 101) were stained by immunohistochemistry for key regulators of retinoic acid (RA) signaling, including ALDH1A2. Survival with respect to these regulators was investigated by univariate Kaplan-Meier analysis and multivariate Cox regression proportional hazard models. The impact of ALDH1A2-RAR signaling on tumor-relevant processes was addressed in established tumor cell lines and in an orthotopic mouse xenograft model. RESULTS: Immunohistochemical analysis showed an improved prognosis of ALDH1A2(high) OPSCC only in the presence of CRABP2, an intracellular RA transporter. Moreover, an ALDH1A2(high)CRABP2(high) staining pattern served as an independent predictor for progression-free (HR: 0.395, p = 0.007) and overall survival (HR: 0.303, p = 0.002), suggesting a critical impact of RA metabolism and signaling on clinical outcome. Functionally, ALDH1A2 expression and activity in tumor cell lines were related to RA levels. While administration of retinoids inhibited clonogenic growth and proliferation, the pharmacological inhibition of ALDH1A2-RAR signaling resulted in loss of cell-cell adhesion and a mesenchymal-like phenotype. Xenograft tumors derived from FaDu cells with stable silencing of ALDH1A2 and primary tumors from OPSCC patients with low ALDH1A2 expression exhibited a mesenchymal-like phenotype characterized by vimentin expression. CONCLUSIONS: This study has unraveled a critical role of ALDH1A2-RAR signaling in the pathogenesis of head and neck cancer and our data implicate that patients with ALDH1A2(low) tumors might benefit from adjuvant treatment with retinoids.

Statistical signal extraction using stable processes

The standard models for statistical signal extraction assume that the signal and noise are generated by linear Gaussian processes. The optimum filter weights for those models are derived using the method of minimum mean square error. In the present work we study the properties of signal extraction models under the assumption that signal/noise are generated by symmetric stable processes. The optimum filter is obtained by the method of minimum dispersion. The performance of the new filter is compared with their Gaussian counterparts by simulation.

Studies on Advanced Oxidation Processes for the Removal of Acetamiprid from Wastewater

Pollution of water with pesticides has become a threat to the man, material and environment. The pesticides released to the environment reach the water bodies through run off. Industrial wastewater from pesticide manufacturing industries contains pesticides at higher concentration and hence a major source of water pollution. Pesticides create a lot of health and environmental hazards which include diseases like cancer, liver and kidney disorders, reproductive disorders, fatal death, birth defects etc. Conventional wastewater treatment plants based on biological treatment are not efficient to remove these compounds to the desired level. Most of the pesticides are phyto-toxic i.e., they kill the microorganism responsible for the degradation and are recalcitrant in nature. Advanced oxidation process (AOP) is a class of oxidation techniques where hydroxyl radicals are employed for oxidation of pollutants. AOPs have the ability to totally mineralise the organic pollutants to CO2 and water. Different methods are employed for the generation of hydroxyl radicals in AOP systems. Acetamiprid is a neonicotinoid insecticide widely used to control sucking type insects on crops such as leafy vegetables, citrus fruits, pome fruits, grapes, cotton, ornamental flowers. It is now recommended as a substitute for organophosphorous pesticides. Since its use is increasing, its presence is increasingly found in the environment. It has high water solubility and is not easily biodegradable. It has the potential to pollute surface and ground waters. Here, the use of AOPs for the removal of acetamiprid from wastewater has been investigated. Five methods were selected for the study based on literature survey and preliminary experiments conducted. Fenton process, UV treatment, UV/ H2O2 process, photo-Fenton and photocatalysis using TiO2 were selected for study. Undoped TiO2 and TiO2 doped with Cu and Fe were prepared by sol-gel method. Characterisation of the prepared catalysts was done by X-ray diffraction, scanning electron microscope, differential thermal analysis and thermogravimetric analysis. Influence of major operating parameters on the removal of acetamiprid has been investigated. All the experiments were designed using central compoiste design (CCD) of response surface methodology (RSM). Model equations were developed for Fenton, UV/ H2O2, photo-Fenton and photocatalysis for predicting acetamiprid removal and total organic carbon (TOC) removal for different operating conditions. Quality of the models were analysed by statistical methods. Experimental validations were also done to confirm the quality of the models. Optimum conditions obtained by experiment were verified with that obtained using response optimiser. Fenton Process is the simplest and oldest AOP where hydrogen peroxide and iron are employed for the generation of hydroxyl radicals. Influence of H2O2 and Fe2+ on the acetamiprid removal and TOC removal by Fenton process were investigated and it was found that removal increases with increase in H2O2 and Fe2+ concentration. At an initial concentration of 50 mg/L acetamiprid, 200 mg/L H2O2 and 20 mg/L Fe2+ at pH 3 was found to be optimum for acetamiprid removal. For UV treatment effect of pH was studied and it was found that pH has not much effect on the removal rate. Addition of H2O2 to UV process increased the removal rate because of the hydroxyl radical formation due to photolyis of H2O2. An H2O2 concentration of 110 mg/L at pH 6 was found to be optimum for acetamiprid removal. With photo-Fenton drastic reduction in the treatment time was observed with 10 times reduction in the amount of reagents required. H2O2 concentration of 20 mg/L and Fe2+ concentration of 2 mg/L was found to be optimum at pH 3. With TiO2 photocatalysis improvement in the removal rate was noticed compared to UV treatment. Effect of Cu and Fe doping on the photocatalytic activity under UV light was studied and it was observed that Cu doping enhanced the removal rate slightly while Fe doping has decreased the removal rate. Maximum acetamiprid removal was observed for an optimum catalyst loading of 1000 mg/L and Cu concentration of 1 wt%. It was noticed that mineralisation efficiency of the processes is low compared to acetamiprid removal efficiency. This may be due to the presence of stable intermediate compounds formed during degradation Kinetic studies were conducted for all the treatment processes and it was found that all processes follow pseudo-first order kinetics. Kinetic constants were found out from the experimental data for all the processes and half lives were calculated. The rate of reaction was in the order, photo- Fenton>UV/ H2O2>Fenton> TiO2 photocatalysis>UV. Operating cost was calculated for the processes and it was found that photo-Fenton removes the acetamiprid at lowest operating cost in lesser time. A kinetic model was developed for photo-Fenton process using the elementary reaction data and mass balance equations for the species involved in the process. Variation of acetamiprid concentration with time for different H2O2 and Fe2+ concentration at pH 3 can be found out using this model. The model was validated by comparing the simulated concentration profiles with that obtained from experiments. This study established the viability of the selected AOPs for the removal of acetamiprid from wastewater. Of the studied AOPs photo- Fenton gives the highest removal efficiency with lowest operating cost within shortest time.