Cue-dependent circuits for illusory contours in humans.

NlmCategory="UNASSIGNED">Objects' borders are readily perceived despite absent contrast gradients, e.g. due to poor lighting or occlusion. In humans, a visual evoked potential (VEP) correlate of illusory contour (IC) sensitivity, the "IC effect", has been identified with an onset at ~90ms and generators within bilateral lateral occipital cortices (LOC). The IC effect is observed across a wide range of stimulus parameters, though until now it always involved high-contrast achromatic stimuli. Whether IC perception and its brain mechanisms differ as a function of the type of stimulus cue remains unknown. Resolving such will provide insights on whether there is a unique or multiple solutions to how the brain binds together spatially fractionated information into a cohesive perception. Here, participants discriminated IC from no-contour (NC) control stimuli that were either comprised of low-contrast achromatic stimuli or instead isoluminant chromatic contrast stimuli (presumably biasing processing to the magnocellular and parvocellular pathways, respectively) on separate blocks of trials. Behavioural analyses revealed that ICs were readily perceived independently of the stimulus cue-i.e. when defined by either chromatic or luminance contrast. VEPs were analysed within an electrical neuroimaging framework and revealed a generally similar timing of IC effects across both stimulus contrasts (i.e. at ~90ms). Additionally, an overall phase shift of the VEP on the order of ~30ms was consistently observed in response to chromatic vs. luminance contrast independently of the presence/absence of ICs. Critically, topographic differences in the IC effect were observed over the ~110-160ms period; different configurations of intracranial sources contributed to IC sensitivity as a function of stimulus contrast. Distributed source estimations localized these differences to LOC as well as V1/V2. The present data expand current models by demonstrating the existence of multiple, cue-dependent circuits in the brain for generating perceptions of illusory contours.

In cortical neurons HDAC3 suppresses RD4-dependent SMRT export

The transcriptional corepressor SMRT controls neuronal responsiveness of several transcription factors and can regulate neuroprotective and neurogenic pathways. SMRT is a multi-domain protein that complexes with HDAC3 as well as being capable of interactions with HDACs 1, 4, 5 and 7. We previously showed that in rat cortical neurons, nuclear localisation of SMRT requires histone deacetylase activity: Inhibition of class I/II HDACs by treatment with trichostatin A (TSA) causes redistribution of SMRT to the cytoplasm, and potentiates the activation of SMRT-repressed nuclear receptors. Here we have sought to identify the HDAC(s) and region(s) of SMRT responsible for anchoring it in the nucleus under normal circumstances and for mediating nuclear export following HDAC inhibition. We show that in rat cortical neurons SMRT export can be triggered by treatment with the class I-preferring HDAC inhibitor valproate and the HDAC2/3-selective inhibitor apicidin, and by HDAC3 knockdown, implicating HDAC3 activity as being required to maintain SMRT in the nucleus. HDAC3 interaction with SMRT's deacetylation activation domain (DAD) is known to be important for activation of HDAC3 deacetylase function. Consistent with a role for HDAC3 activity in promoting SMRT nuclear localization, we found that inactivation of SMRT's DAD by deletion or point mutation triggered partial redistribution of SMRT to the cytoplasm. We also investigated whether other regions of SMRT were involved in mediating nuclear export following HDAC inhibition. TSA- and valproate-induced SMRT export was strongly impaired by deletion of its repression domain-4 (RD4). Furthermore, over-expression of a region of SMRT containing the RD4 region suppressed TSA-induced export of full-length SMRT. Collectively these data support a model whereby SMRT's RD4 region can recruit factors capable of mediating nuclear export of SMRT, but whose function and/or recruitment is suppressed by HDAC3 activity. Furthermore, they underline the fact that HDAC inhibitors can cause reorganization and redistribution of corepressor complexes.

Analysis of space-time environmental data in complex regions

This thesis develops a comprehensive and a flexible statistical framework for the analysis and detection of space, time and space-time clusters of environmental point data. The developed clustering methods were applied in both simulated datasets and real-world environmental phenomena; however, only the cases of forest fires in Canton of Ticino (Switzerland) and in Portugal are expounded in this document. Normally, environmental phenomena can be modelled as stochastic point processes where each event, e.g. the forest fire ignition point, is characterised by its spatial location and occurrence in time. Additionally, information such as burned area, ignition causes, landuse, topographic, climatic and meteorological features, etc., can also be used to characterise the studied phenomenon. Thereby, the space-time pattern characterisa- tion represents a powerful tool to understand the distribution and behaviour of the events and their correlation with underlying processes, for instance, socio-economic, environmental and meteorological factors. Consequently, we propose a methodology based on the adaptation and application of statistical and fractal point process measures for both global (e.g. the Morisita Index, the Box-counting fractal method, the multifractal formalism and the Ripley's K-function) and local (e.g. Scan Statistics) analysis. Many measures describing the space-time distribution of environmental phenomena have been proposed in a wide variety of disciplines; nevertheless, most of these measures are of global character and do not consider complex spatial constraints, high variability and multivariate nature of the events. Therefore, we proposed an statistical framework that takes into account the complexities of the geographical space, where phenomena take place, by introducing the Validity Domain concept and carrying out clustering analyses in data with different constrained geographical spaces, hence, assessing the relative degree of clustering of the real distribution. Moreover, exclusively to the forest fire case, this research proposes two new methodologies to defining and mapping both the Wildland-Urban Interface (WUI) described as the interaction zone between burnable vegetation and anthropogenic infrastructures, and the prediction of fire ignition susceptibility. In this regard, the main objective of this Thesis was to carry out a basic statistical/- geospatial research with a strong application part to analyse and to describe complex phenomena as well as to overcome unsolved methodological problems in the characterisation of space-time patterns, in particular, the forest fire occurrences. Thus, this Thesis provides a response to the increasing demand for both environmental monitoring and management tools for the assessment of natural and anthropogenic hazards and risks, sustainable development, retrospective success analysis, etc. The major contributions of this work were presented at national and international conferences and published in 5 scientific journals. National and international collaborations were also established and successfully accomplished. -- Cette thèse développe une méthodologie statistique complète et flexible pour l'analyse et la détection des structures spatiales, temporelles et spatio-temporelles de données environnementales représentées comme de semis de points. Les méthodes ici développées ont été appliquées aux jeux de données simulées autant qu'A des phénomènes environnementaux réels; nonobstant, seulement le cas des feux forestiers dans le Canton du Tessin (la Suisse) et celui de Portugal sont expliqués dans ce document. Normalement, les phénomènes environnementaux peuvent être modélisés comme des processus ponctuels stochastiques ou chaque événement, par ex. les point d'ignition des feux forestiers, est déterminé par son emplacement spatial et son occurrence dans le temps. De plus, des informations tels que la surface bru^lée, les causes d'ignition, l'utilisation du sol, les caractéristiques topographiques, climatiques et météorologiques, etc., peuvent aussi être utilisées pour caractériser le phénomène étudié. Par conséquent, la définition de la structure spatio-temporelle représente un outil puissant pour compren- dre la distribution du phénomène et sa corrélation avec des processus sous-jacents tels que les facteurs socio-économiques, environnementaux et météorologiques. De ce fait, nous proposons une méthodologie basée sur l'adaptation et l'application de mesures statistiques et fractales des processus ponctuels d'analyse global (par ex. l'indice de Morisita, la dimension fractale par comptage de boîtes, le formalisme multifractal et la fonction K de Ripley) et local (par ex. la statistique de scan). Des nombreuses mesures décrivant les structures spatio-temporelles de phénomènes environnementaux peuvent être trouvées dans la littérature. Néanmoins, la plupart de ces mesures sont de caractère global et ne considèrent pas de contraintes spatiales com- plexes, ainsi que la haute variabilité et la nature multivariée des événements. A cet effet, la méthodologie ici proposée prend en compte les complexités de l'espace géographique ou le phénomène a lieu, à travers de l'introduction du concept de Domaine de Validité et l'application des mesures d'analyse spatiale dans des données en présentant différentes contraintes géographiques. Cela permet l'évaluation du degré relatif d'agrégation spatiale/temporelle des structures du phénomène observé. En plus, exclusif au cas de feux forestiers, cette recherche propose aussi deux nouvelles méthodologies pour la définition et la cartographie des zones périurbaines, décrites comme des espaces anthropogéniques à proximité de la végétation sauvage ou de la forêt, et de la prédiction de la susceptibilité à l'ignition de feu. A cet égard, l'objectif principal de cette Thèse a été d'effectuer une recherche statistique/géospatiale avec une forte application dans des cas réels, pour analyser et décrire des phénomènes environnementaux complexes aussi bien que surmonter des problèmes méthodologiques non résolus relatifs à la caractérisation des structures spatio-temporelles, particulièrement, celles des occurrences de feux forestières. Ainsi, cette Thèse fournit une réponse à la demande croissante de la gestion et du monitoring environnemental pour le déploiement d'outils d'évaluation des risques et des dangers naturels et anthro- pogéniques. Les majeures contributions de ce travail ont été présentées aux conférences nationales et internationales, et ont été aussi publiées dans 5 revues internationales avec comité de lecture. Des collaborations nationales et internationales ont été aussi établies et accomplies avec succès.

Tuotetiedon soveltaminen varastotiedon hallinnan parantamisessa

Inventory data management is defined as an accurate creation and maintenance of item master data, inventory location data and inventory balances per an inventory location. The accuracy of inventory data is dependent of many elements of the product data management like the management of changes during a component’s life-cycle and the accuracy of product configuration in enterprise resource planning systems. Cycle-counting is counting of inventory balances per an inventory location and comparing them to the system data on a daily basis. The Cycle-counting process is a way to measure the accuracy of the inventory data in a company. Through well managed cycle-counting process a company gets a lot of information of their inventory data accuracy. General inaccuracy of the inventory data can’t be fixed through only assigning resources to the cycle-counting but the change requires disciplined following of the defined processes from all parties involved in updating inventory data through a component’s life-cycle. The Processes affecting inventory data are mapped and the appropriate metrics are defined in order to achieve better manageability of the inventory data. The Life-cycles of a single component and of a product are used in evaluation of the processes.

Case-Crossover Analysis of Air Pollution Health Effects: A Systematic Review of Methodology and Application

Case-crossover is one of the most used designs for analyzing the health-related effects of air pollution. Nevertheless, no one has reviewed its application and methodology in this context. Objective: We conducted a systematic review of case-crossover (CCO) designs used to study the relationship between air pollution and morbidity and mortality, from the standpoint of methodology and application.Data sources and extraction: A search was made of the MEDLINE and EMBASE databases.Reports were classified as methodologic or applied. From the latter, the following information was extracted: author, study location, year, type of population (general or patients), dependent variable(s), independent variable(s), type of CCO design, and whether effect modification was analyzed for variables at the individual level. Data synthesis: The review covered 105 reports that fulfilled the inclusion criteria. Of these, 24 addressed methodological aspects, and the remainder involved the design’s application. In the methodological reports, the designs that yielded the best results in simulation were symmetric bidirectional CCO and time-stratified CCO. Furthermore, we observed an increase across time in the use of certain CCO designs, mainly symmetric bidirectional and time-stratified CCO. The dependent variables most frequently analyzed were those relating to hospital morbidity; the pollutants most often studied were those linked to particulate matter. Among the CCO-application reports, 13.6% studied effect modification for variables at the individual level.Conclusions: The use of CCO designs has undergone considerable growth; the most widely used designs were those that yielded better results in simulation studies: symmetric bidirectional and time-stratified CCO. However, the advantages of CCO as a method of analysis of variables at the individual level are put to little use

Role of human hydroxysteroid (17beta) dehydrogenase type 1 (HSD17B1) in steroid-dependent diseases in females –novel indications for HSD17B1 inhibitors. Phenotypic analysis of transgenic mice overexpressing human HSD17B1.

Hormone-dependent diseases, e.g. cancers, rank high in mortality in the modern world, and thus, there is an urgent need for new drugs to treat these diseases. Although the diseases are clearly hormone-dependent, changes in circulating hormone concentrations do not explain all the pathological processes observed in the diseased tissues. A more inclusive explanation is provided by intracrinology – a regulation of hormone concentrations at the target tissue level. This is mediated by the expression of a pattern of steroid-activating and -inactivating enzymes in steroid target tissues, thus enabling a concentration gradient between the blood circulation and the tissue. Hydroxysteroid (17beta) dehydrogenases (HSD17Bs) form a family of enzymes that catalyze the conversion between low active 17-ketosteroids and highly active 17beta-hydroxysteroids. HSD17B1 converts low active estrogen (E1) to highly active estradiol (E2) with high catalytic efficiency, and altered HSD17B1 expression has been associated with several hormone-dependent diseases, including breast cancer, endometriosis, endometrial hyperplasia and cancer, and ovarian epithelial cancer. Because of its putative role in E2 biosynthesis in ovaries and peripheral target tissues, HSD17B1 is considered to be a promising drug target for estrogen-dependent diseases. A few studies have indicated that the enzyme also has androgenic activity, but they have been ignored. In the present study, transgenic mice overexpressing human HSD17B1 (HSD17B1TG mice) were used to study the effects of the enzyme in vivo. Firstly, the substrate specificity of human HSD17B1 was determined in vivo. The results indicated that human HSD17B1 has significant androgenic activity in female mice in vivo, which resulted in increased fetal testosterone concentration and female disorder of sexual development appearing as masculinized phenotype (increased anogenital distance, lack of nipples, lack of vaginal opening, combination of vagina with urethra, enlarged Wolffian duct remnants in the mesovarium and enlarged female prostate). Fetal androgen exposure has been linked to polycystic ovary syndrome (PCOS) and metabolic syndrome during adulthood in experimental animals and humans, but the genes involved in PCOS are largely unknown. A putative mechanism to accumulate androgens during fetal life by HSD17B1 overexpression was shown in the present study. Furthermore, as a result of prenatal androgen exposure locally in the ovaries, HSD17B1TG females developed ovarian benign serous cystadenomas in adulthood. These benign lesions are precursors of low-grade ovarian serous tumors. Ovarian cancer ranks fifth in mortality of all female cancers in Finland, and most of the ovarian cancers arise from the surface epithelium. The formation of the lesions was prevented by prenatal antiandrogen treatment and by transplanting wild type (WT) ovaries prepubertally into HSD17B1TG females. The results obtained in our non-clinical TG mouse model, together with a literature analysis, suggest that HSD17B1 has a role in ovarian epithelial carcinogenesis, and especially in the development of serous tumors. The role of androgens in ovarian carcinogenesis is considered controversial, but the present study provides further evidence for the androgen hypothesis. Moreover, it directly links HSD17B1-induced prenatal androgen exposure to ovarian epithelial carcinogenesis in mice. As expected, significant estrogenic activity was also detected for human HSD17B1. HSD17B1TG mice had enhanced peripheral conversion of E1 to E2 in a variety of target tissues, including the uterus. Furthermore, this activity was significantly decreased by treatments with specific HSD17B1 inhibitors. As a result, several estrogen-dependent disorders were found in HSD17B1TG females. Here we report that HSD17B1TG mice invariably developed endometrial hyperplasia and failed to ovulate in adulthood. As in humans, endometrial hyperplasia in HSD17B1TG females was reversible upon ovulation induction, triggering a rise in circulating progesterone levels, and in response to exogenous progestins. Remarkably, treatment with a HSD17B1 inhibitor failed to restore ovulation, yet completely reversed the hyperplastic morphology of epithelial cells in the glandular compartment. We also demonstrate that HSD17B1 is expressed in normal human endometrium, hyperplasia, and cancer. Collectively, our non-clinical data and literature analysis suggest that HSD17B1 inhibition could be one of several possible approaches to decrease endometrial estrogen production in endometrial hyperplasia and cancer. HSD17B1 expression has been found in bones of humans and rats. The non-clinical data in the present study suggest that human HSD17B1 is likely to have an important role in the regulation of bone formation, strength and length during reproductive years in female mice. Bone density in HSD17B1TG females was highly increased in femurs, but in lesser amounts also in tibias. Especially the tibia growth plate, but not other regions of bone, was susceptible to respond to HSD17B1 inhibition by increasing bone length, whereas the inhibitors did not affect bone density. Therefore, HSD17B1 inhibitors could be safer than aromatase inhibitors in regard to bone in the treatment of breast cancer and endometriosis. Furthermore, diseases related to improper growth, are a promising new indication for HSD17B1 inhibitors.

Creative Industries: a Preliminary Insight to their Location Determinants

This paper is about location decisions of Creative Industries and the role played by existent spatial distribution and agglomeration economies of these kinds of activities in order to analyse their location determinants. Our main statistical source is the REIC (Catalan Manufacturing Establishments Register), which has plant-level microdata on location of new plants. Using Count Data Models, our main results show that location determinants are quite similar between both industries and also both non-creative and creative firms are positively influenced by the specialisation level in Creative Industries of municipalities. Moreover, our results provide evidence that the unobserved ‘creative milieu’ has a limited impact on attracting firms. Keywords: creative industries, creative milieu, count data models, industrial location, agglomeration economies

Advanced chemometric methods: Applicability on industrial data

Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

Supercritical CO2 recovery of caffeine from green coffee oil: new experimental solubility data and modeling

The caffeine solubility in supercritical CO2 was studied by assessing the effects of pressure and temperature on the extraction of green coffee oil (GCO). The Peng-Robinson¹ equation of state was used to correlate the solubility of caffeine with a thermodynamic model and two mixing rules were evaluated: the classical mixing rule of van der Waals with two adjustable parameters (PR-VDW) and a density dependent one, proposed by Mohamed and Holder² with two (PR-MH, two parameters adjusted to the attractive term) and three (PR-MH3 two parameters adjusted to the attractive and one to the repulsive term) adjustable parameters. The best results were obtained with the mixing rule of Mohamed and Holder² with three parameters.

An undergraduate level experiment on the synthesis of Au nanoparticles and their size-dependent optical and catalytic properties

The synthesis of gold nanoparticles (Au NPs) 15, 26, and 34 nm in diameter, followed by the investigation of their size-dependent optical and catalytic properties, is described herein as an undergraduate level experiment. The proposed experiment covers concepts on the synthesis, stabilization, and characterization of Au NPs, their size-dependent optical and catalytic properties at the nanoscale, chemical kinetics, and the role of a catalyst. The experiment should be performed by groups of two or three students in three lab sessions of 3 h each and organized as follows: i) synthesis of Au NPs of different sizes and investigation of their optical properties; ii) evaluation of their catalytic activity; and iii) data analysis and discussion. We believe that this activity enables students to integrate these multidisciplinary concepts in a single experiment as well as to become introduced/familiarized with an active research field and current literature in the areas of nanoparticle synthesis and catalysis.

Determining the location for a mobile device by utilization of local resources of the environment

The subject being analyzed of this Master’s Thesis is a development of a service that is used to define a current location of a mobile device. The service utilized data that is obtained from own GPS receiver in some possible cases and as well data from mobile devices which can be afforded for the current environment for acquisition of more precise position of the device. The computation environment is based on context of a mobile device. The service is implemented as an application for communicator series Nokia N8XX. The Master’s Thesis presents theoretical concept of the method and its practical implementation, architecture of the application, requirements and describes a process of its functionality. Also users’ work with application is presented and recommendations for possible future improvements are made.

Creating carbon footprint calculating tool for plastic packaging products

The environmental challenges of plastic packaging industry have increased remarkably along with climate change debate. The interest to study carbon footprints of packaging has increased in packaging industry to find out the real climate change impacts of packaging. In this thesis the greenhouse gas discharges of plastic packaging during their life cycle is examined. The carbon footprint is calculated for food packaging manufactured from plastic laminate. The structure of the laminate is low density polyethylene (PE-LD) and oriented polypropylene (OPP), which have been joined together with laminating adhesive. The purpose is to find out the possibilities to create a carbon footprint calculating tool for plastic packaging and its usability in a plastic packaging manufacturing company. As a carbon footprint calculating method PAS 2050 standard has been used. In the calculations direct and indirect greenhouse gas discharges as well as avoided discharges are considered. Avoided discharges are born for example in packaging waste utilization as energy. The results of the calculations have been used to create a simple calculating tool to be used for similar laminate structures. Although the utilization of the calculating tool is limited to one manufacturing plant because the primary activity data is dependent of geographical location and for example the discharges of used energy in the plant. The results give an approximation of the climate change potential caused by the laminate. It is although noticed that calculations do not include all environmental impacts of plastic packaging´s life cycle.

Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil

ABSTRACTChanges in the frequency of occurrence of extreme weather events have been pointed out as a likely impact of global warming. In this context, this study aimed to detect climate change in series of extreme minimum and maximum air temperature of Pelotas, State of Rio Grande do Sul, (1896 - 2011) and its influence on the probability of occurrence of these variables. We used the general extreme value distribution (GEV) in its stationary and non-stationary forms. In the latter case, GEV parameters are variable over time. On the basis of goodness-of-fit tests and of the maximum likelihood method, the GEV model in which the location parameter increases over time presents the best fit of the daily minimum air temperature series. Such result describes a significant increase in the mean values of this variable, which indicates a potential reduction in the frequency of frosts. The daily maximum air temperature series is also described by a non-stationary model, whose location parameter decreases over time, and the scale parameter related to sample variance rises between the beginning and end of the series. This result indicates a drop in the mean of daily maximum air temperature values and increased dispersion of the sample data.

Strategic outsourcing of R&D: The location-specific advantages of India to the pharmaceutical industry

Companies are increasingly under pressure to be more efficient both in terms of costs and overall performance and thus, they seek new ways to develop their products and innovate. For pharmaceutical industry it can take several decades to launch a new drug to the markets. Since pharmaceutical industry is one of the most research-intensive industries, is outsourcing one way to enhance the R&D processes of such companies. It is said that outsourcing to offshore locations is vastly more challenging and complicated than any other exporting activity or inter-company relationship that has evoked a lot of discussion. By outsourcing strategically, companies must also thoroughly focus on transaction costs and core competences. Today, the suppliers are looked for beyond national boundaries and furthermore, the location of the outsourcing activity must also be thoroughly considered. Consequently, the purpose of this study is to analyze what is known of strategic outsourcing of pharmaceutical R&D to India. In order to meet the purpose of the study, this study tries to answer three sub-questions set to it: first, what is strategic outsourcing, second, why pharmaceutical companies utilize strategic outsourcing of R&D and last, why pharmaceutical companies select India as the location for outsourcing their R&D. The study is a qualitative study. The purpose of the study was approached by a literature review with systematic elements and sub-questions were analyzed through different relevant theories, such as theory of transaction costs, core competences and location advantages. Applicable academic journal articles were comprehensively included in the study. The data was collected from electronic journal article databases using key words and almost only peer-reviewed, as new as possible articles were included. Also both the reference list of the included articles and article recommendations from professionals generated more articles for inclusion. The data was analyzed through thematization that resulted in themes that illuminate the purpose of the study and sub-questions. As an outcome of the analysis, each of the theory chapters in the study represents one sub-question. The literature used in this study revealed that strategic outsourcing of R&D is increasingly used in pharmaceutical industry and the major motives to practice it has to do with lowering costs, accessing skilled labor, resources and knowledge and enhancing their quality while speeding up the introduction of new drugs. Mainly for the above-mentioned motives India is frequently chosen as the target location for pharma outsourcers. Still, the literature is somewhat incomplete in this complex phenomenon and more research is needed.

Retrospective canine skin peripheral nerve sheath tumors data with emphasis on histologic, immunohistochemical and prognostic factors

Abstract: In this retrospective study was determined the frequency of canine skin peripheral nerve sheath tumors (PNST) in cases diagnosed by the Setor de Patologia Veterinária of the Universidade Federal do Rio Grande do Sul (SPV-UFRGS), Brazil, between the years 2000 and 2012. The canine profiles, as well as histological, immunohistochemical and prognostic aspects of the tumors were based on 70 samples, comprising 40 females, 29 males and one unspecified sample. Between 2000 and 2012, 2,984 skin tumors of dogs were diagnosed in the SPV-UFRGS, totaling 2.34% of skin neoplasms in dogs. Animals that comprised the largest amount of samples (43%) were those with no breed (SRD), followed by German Shepherds (10%). Females were more affected than males (40/70 - 57% and 29/70 - 41% respectively). Skin PNST of this research showed predominant localization on the limbs (40% in the forelimbs and 29% in the hindlimbs); affecting adult dogs, mostly aged between 8 and 11 years (54%). The samples were routinely processed for hematoxylin and eosin, and were also evaluated by toluidine blue and Masson's trichrome staining, and immunohistochemistry (IHC) anti-vimentin, -S-100, -GFAP, -actin, von Willebrand factor and neurofilament. Anisocytosis and anisokaryosis, mitotic index, intratumoral necrosis, invasion of adjacent tissues, tumor location, local recurrence and metastasis were related to the diagnosis of benign (49/70) or malignant tumor (21/70). The Antoni A histological pattern was observed more frequently in benign tumors. The immunohistochemistry helped to diagnose PNST, and anti-vimentin and anti-protein S-100 showed the highest rates of immunostaining. Throughout statistical analysis of animals with tumor recurrence, it was found that the chance of an animal with a malignant peripheral nerve sheath tumor to develop recurrence is 4.61 times higher than in an animal that had a benign tumor.