Clinical pharmacology of the angiotensin II receptor antagonist losartan potassium in healthy subjects

INTRODUCTION: The evaluation of a new drug in normotensive volunteers provides important pharmacodynamic and pharmacokinetic information as long as the compound has a specific mechanism of action which can be evaluated in healthy subjects as well as in patients. The purpose of the present paper is to discuss the results that have been obtained in normal volunteers with the specific angiotensin II receptor antagonist, losartan potassium. DOSE-FINDING: Over the last few years, studies in normotensive subjects have demonstrated that the minimal dose of losartan that produces maximal efficacy is 40-80 mg. Losartan has a long duration of action and its ability to produce a sustained blockade of the renin-angiotensin system is due almost exclusively to the active metabolite E3174. HORMONAL EFFECTS: Angiotensin II receptor blockade with losartan induces an expected increase in plasma renin activity and plasma angiotensin II levels. A decrease in plasma aldosterone levels has been found only with a high dose of losartan (120 mg). RENAL AND BLOOD PRESSURE EFFECTS: In normotensive subjects, losartan has little or no effect on blood pressure unless the subjects are markedly salt-depleted. Losartan causes no change in the glomerular filtration rate and either no modification or only a slight increase in renal blood flow. Losartan significantly increases urinary sodium excretion, however, and surprisingly produces a transient rise in urinary potassium excretion. Finally, losartan increases uric acid excretion and lowers plasma uric acid levels. CONCLUSIONS: These results suggest that losartan is an effective angiotensin II receptor antagonist in normal subjects. Its safety and clinical efficacy in hypertensive patients will be addressed in large clinical trials.

Iron-deficiency anemia and hematochezia: when is colonoscopy appropriate?

Background: Colonoscopy is usually proposed for the evaluation of lower gastrointestinal blood loss (hematochezia) or iron deficiency anemia (IDA). Clinical practice guidelines support this approach but formal evidence is lacking. Real clinical scenarios made available on the web would be of great help in decision-making in clinical practice as to whether colonoscopy is appropriate for a given patient. Method: A multidisciplinary multinational expert panel (EPAGE II) developed appropriateness criteria based on best published evidence (systematic reviews, clinical trials, guidelines) and experts' judgement. Using the explicit RAND Appropriateness Method (3 round of experts' votes and a panel meeting) 102 clinical scenarios were judged inappropriate, uncertain, appropriate, or necessary. Results: In IDA, colonoscopy was appropriate in patients >50 years and necessary in the presence of lower abdominal symptoms. In both men and women aged <50 years, colonoscopy was appropriate if prior sigmoidoscopy and/or gastroscopy did not explain the IDA, and necessary if lower gastrointestinal symptoms were present. In women <50 years with a potential gynecological cause, additional lower gastrointestinal symptoms rendered colonoscopy appropriate. In patients >50 years with hematochezia, colonoscopy was always appropriate and mostly necessary, except if a prior colonoscopy was normal within the previous 5 years. Under age 50 years, the presence of any risk factor for colorectal cancer (CRC) and no previous normal colonoscopy (within the last 5 years) made this procedure appropriate and necessary. Conclusion: Colonoscopy is appropriate and even necessary for many indications related to iron deficiency anemia or hematochezia, in particular in patients aged >50 years. The main factors influencing appropriateness are age, results of prior investigations (sigmoidoscopy, gastroscopy, previous colonoscopy), CRC risk and sex. EPAGE II appropriateness criteria are available on www.epage.ch

Pseudomonas aeruginosa serotypes in nosocomial pneumonia: prevalence and clinical outcomes.

INTRODUCTION: Pseudomonas aeruginosa frequently causes nosocomial pneumonia and is associated with poor outcome. The purpose of this study was to assess the prevalence and clinical outcome of nosocomial pneumonia caused by serotype-specific P. aeruginosa in critically ill patients under appropriate antimicrobial therapy management. METHODS: A retrospective, non-interventional epidemiological multicenter cohort study involving 143 patients with confirmed nosocomial pneumonia caused by P. aeruginosa. Patients were analyzed for a period of 30 days from time of nosocomial pneumonia onset. Fourteen patients fulfilling the same criteria from a phase IIa studyconducted at the same time/centers were included in the prevalence calculations but not in the clinical outcome analysis. RESULTS: The prevalence of serotypes was: O6 (29%), O11 (23%), O10 (10%), O2 (9%), and O1 (8%). Serotypes with a prevalence of less than 5% were found in 13% of patients, 8% were classified as not typeable. Across all serotypes, 19% mortality, 70% clinical resolution, 11% clinical continuation, and 5% clinical recurrence were recorded. Age and higher APACHE II (Acute Physiology and Chronic Health Evaluation II) were predictive risk factors associated with probability of death and lower clinical resolution for P. aeruginosa nosocomial pneumonia. Mortality tends to be higher with O1 (40%) and lower with O2 (0%); clinical resolution tends to be better with O2 (82%) compared to other serotypes. Persisting pneumonia with O6 and O11 was, respectively, 8% and 21%; clinical resolution with O6 and O11 was, respectively, 75% and 57%. CONCLUSIONS: In P. aeruginosa nosocomial pneumonia, the most prevalent serotypes were O6 and O11. Further studies including larger group sizes are needed to correlate clinical outcome with virulence factors of P. aeruginosa in patients with nosocomial pneumonia caused by various serotypes; and to compare O6 and O11, the two serotypes most frequently encountered in critically ill patients.

Optimization and Management of Materials in Earthwork Construction, TR-501, 2010

As a result of forensic investigations of problems across Iowa, a research study was developed aimed at providing solutions to identified problems through better management and optimization of the available pavement geotechnical materials and through ground improvement, soil reinforcement, and other soil treatment techniques. The overall goal was worked out through simple laboratory experiments, such as particle size analysis, plasticity tests, compaction tests, permeability tests, and strength tests. A review of the problems suggested three areas of study: pavement cracking due to improper management of pavement geotechnical materials, permeability of mixed-subgrade soils, and settlement of soil above the pipe due to improper compaction of the backfill. This resulted in the following three areas of study: (1) The optimization and management of earthwork materials through general soil mixing of various select and unsuitable soils and a specific example of optimization of materials in earthwork construction by soil mixing; (2) An investigation of the saturated permeability of compacted glacial till in relation to validation and prediction with the Enhanced Integrated Climatic Model (EICM); and (3) A field investigation and numerical modeling of culvert settlement. For each area of study, a literature review was conducted, research data were collected and analyzed, and important findings and conclusions were drawn. It was found that optimum mixtures of select and unsuitable soils can be defined that allow the use of unsuitable materials in embankment and subgrade locations. An improved model of saturated hydraulic conductivity was proposed for use with glacial soils from Iowa. The use of proper trench backfill compaction or the use of flowable mortar will reduce the potential for developing a bump above culverts.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Subjective mental time: the functional architecture of projecting the self to past and future.

Abstract Human experience takes place in the line of mental time (MT) created through 'self-projection' of oneself to different time-points in the past or future. Here we manipulated self-projection in MT not only with respect to one's life events but also with respect to one's faces from different past and future time-points. Behavioural and event-related functional magnetic resonance imaging activity showed three independent effects characterized by (i) similarity between past recollection and future imagination, (ii) facilitation of judgements related to the future as compared with the past, and (iii) facilitation of judgements related to time-points distant from the present. These effects were found with respect to faces and events, and also suggest that brain mechanisms of MT are independent of whether actual life episodes have to be re-experienced or pre-experienced, recruiting a common cerebral network including the anteromedial temporal, posterior parietal, inferior frontal, temporo-parietal and insular cortices. These behavioural and neural data suggest that self-projection in time is a fundamental aspect of MT, relying on neural structures encoding memory, mental imagery and self.

Electrical signature of modern and ancient tectonic processes in the crust of the Atlas mountains of Morocco.

The Atlas Mountains in Morocco are considered as type examples of intracontinental chains, with high topography that contrasts with moderate crustal shortening and thickening. Whereas recent geological studies and geodynamic modeling have suggested the existence of dynamic topography to explain this apparent contradiction, there is a lack of modern geophysical data at the crustal scale to corroborate this hypothesis. Newly-acquired magnetotelluric data image the electrical resistivity distribution of the crust from the Middle Atlas to the Anti-Atlas, crossing the tabular Moulouya Plain and the High Atlas. All the units show different and unique electrical signatures throughout the crust reflecting the tectonic history of development of each one. In the upper crust electrical resistivity values may be associated to sediment sequences in the Moulouya and Anti-Atlas and to crustal scale fault systems in the High Atlas developed during the Cenozoic times. In the lower crust the low resistivity anomaly found below the Mouluya plain, together with other geophysical (low velocity anomaly, lack of earthquakes and minimum Bouguer anomaly) and geochemical (Neogene-Quaternary intraplate alkaline volcanic fields) evidence, infer the existence of a small degree of partial melt at the base of the lower crust. The low resistivity anomaly found below the Anti-Atlas may be associated with a relict subduction of Precambrian oceanic sediments, or to precipitated minerals during the release of fluids from the mantle during the accretion of the Anti-Atlas to the West African Supercontinent during the Panafrican orogeny ca. 685 Ma).

ECIL recommendations for the use of biological markers for the diagnosis of invasive fungal diseases in leukemic patients and hematopoietic SCT recipients.

As culture-based methods for the diagnosis of invasive fungal diseases (IFD) in leukemia and hematopoietic SCT patients have limited performance, non-culture methods are increasingly being used. The third European Conference on Infections in Leukemia (ECIL-3) meeting aimed at establishing evidence-based recommendations for the use of biological tests in adult patients, based on the grading system of the Infectious Diseases Society of America. The following biomarkers were investigated as screening tests: galactomannan (GM) for invasive aspergillosis (IA); β-glucan (BG) for invasive candidiasis (IC) and IA; Cryptococcus Ag for cryptococcosis; mannan (Mn) Ag/anti-mannan (A-Mn) Ab for IC, and PCR for IA. Testing for GM, Cryptococcus Ag and BG are included in the revised EORTC/MSG (European Organization for Research and Treatment of Cancer/Mycoses Study Group) consensus definitions for IFD. Strong evidence supports the use of GM in serum (A II), and Cryptococcus Ag in serum and cerebrospinal fluid (CSF) (A II). Evidence is moderate for BG detection in serum (B II), and the combined Mn/A-Mn testing in serum for hepatosplenic candidiasis (B III) and candidemia (C II). No recommendations were formulated for the use of PCR owing to a lack of standardization and clinical validation. Clinical utility of these markers for the early management of IFD should be further assessed in prospective randomized interventional studies.

Watermelon transformation with Zucchini yellow mosaic virus coat protein gene and comparison with parental cultivar

The objective of this work was to transfer Zucchini yellow mosaic virus coat protein (ZYMV-CP) and neomycin phosphotransferase II (NPT II) genes to the watermelon 'Crimson Sweet'(CS) genome, and to compare the transgenic progenies T1 and T2 with the nontransformed parental cultivar for morphological, pomological, growth and yield characteristics. The ZYMV-CP gene was transferred by Agrobacterium tumefaciens. The presence of the gene in transgenic T0, T1 and T2 plants was determined by polymerase chain reaction, and the results were confirmed by Southern blot. Two experiments were performed, one in the winter-spring and the other in the summer-autumn. In both experiments, the hypocotyl length of transgenic seedlings was significantly higher than that of nontransgenic parental ones. In the second experiment, the differences between transgenic and nontransgenic individuals were significant concerning fruit rind thickness, flesh firmness, fruit peduncle length, size of pistil scar, and a* values for fruit stripe or flesh color. Transferring ZYMV-CP gene to CS genome affected only a few characteristics from the 80 evaluated ones. The changes in rind thickness, flesh firmness and flesh color a* values are favorable, while the increase in the size of pistil scar is undesirable. The transgenic watermelon line having ZYMV-CP gene and the parental cultivar CS are very similar.

Structure of the extracellular domains of human and Xenopus Fn14: implications in the evolution of TWEAK and Fn14 interactions.

TWEAK (TNF homologue with weak apoptosis-inducing activity) and Fn14 (fibroblast growth factor-inducible protein 14) are members of the tumor necrosis factor (TNF) ligand and receptor super-families. Having observed that Xenopus Fn14 cross-reacts with human TWEAK, despite its relatively low sequence homology to human Fn14, we examined the conservation in tertiary fold and binding interfaces between the two species. Our results, combining NMR solution structure determination, binding assays, extensive site-directed mutagenesis and molecular modeling, reveal that, in addition to the known and previously characterized β-hairpin motif, the helix-loop-helix motif makes an essential contribution to the receptor/ligand binding interface. We further discuss the insight provided by the structural analyses regarding how the cysteine-rich domains of the TNF receptor super-family may have evolved over time. DATABASE: Structural data are available in the Protein Data Bank/BioMagResBank databases under the accession codes 2KMZ, 2KN0 and 2KN1 and 17237, 17247 and 17252. STRUCTURED DIGITAL ABSTRACT: TWEAK binds to hFn14 by surface plasmon resonance (View interaction) xeFn14 binds to TWEAK by enzyme linked immunosorbent assay (View interaction) TWEAK binds to xeFn14 by surface plasmon resonance (View interaction) hFn14 binds to TWEAK by enzyme linked immunosorbent assay (View interaction).

Compensatory up-regulation of angiotensin II subtype 1 receptors in alpha ENaC knockout heterozygous mice.

BACKGROUND: In mice, a partial loss of function of the epithelial sodium channel (ENaC), which regulates sodium excretion in the distal nephron, causes pseudohypoaldosteronism, a salt-wasting syndrome. The purpose of the present experiments was to examine how alpha ENaC knockout heterozygous (+/-) mice, which have only one allele of the gene encoding for the alpha subunit of ENaC, control their blood pressure (BP) and sodium balance. METHODS: BP, urinary electrolyte excretion, plasma renin activity, and urinary adosterone were measured in wild-type (+/+) and heterozygous (+/-) mice on a low, regular, or high sodium diet. In addition, the BP response to angiotensin II (Ang II) and to Ang II receptor blockade, and the number and affinity of Ang II subtype 1 (AT1) receptors in renal tissue were analyzed in both mouse strains on the three diets. RESULTS: In comparison with wild-type mice (+/+), alpha ENaC heterozygous mutant mice (+/-) showed an intact capacity to maintain BP and sodium balance when studied on different sodium diets. However, no change in plasma renin activity was found in response to changes in sodium intake in alpha ENaC +/- mice. On a normal salt diet, heterozygous mice had an increased vascular responsiveness to exogenous Ang II (P < 0.01). Moreover, on a normal and low sodium intake, these mice exhibited an increase in the number of AT1 receptors in renal tissues; their BP lowered markedly during the Ang II receptor blockade (P < 0.01) and there was a clear tendency for an increase in urinary aldosterone excretion. CONCLUSIONS: alpha ENaC heterozygous mice have developed an unusual mechanism of compensation leading to an activation of the renin-angiotensin system, that is, the up-regulation of AT1 receptors. This up-regulation may be due to an increase in aldosterone production.

Safety of a new algorithm for the management of childhood illness (Almanach) to improve quality of care and rational use of drugs

Introduction New evidence from randomized controlled and etiology of fever studies, the availability of reliable RDT for malaria, and novel technologies call for revision of the IMCI strategy. We developed a new algorithm based on (i) a systematic review of published studies assessing the safety and appropriateness of RDT and antibiotic prescription, (ii) results from a clinical and microbiological investigation of febrile children aged <5 years, (iii) international expert IMCI opinions. The aim of this study was to assess the safety of the new algorithm among patients in urban and rural areas of Tanzania.Materials and Methods The design was a controlled noninferiority study. Enrolled children aged 2-59 months with any illness were managed either by a study clinician using the new Almanach algorithm (two intervention health facilities), or clinicians using standard practice, including RDT (two control HF). At day 7 and day 14, all patients were reassessed. Patients who were ill in between or not cured at day 14 were followed until recovery or death. Primary outcome was rate of complications, secondary outcome rate of antibiotic prescriptions.Results 1062 children were recruited. Main diagnoses were URTI 26%, pneumonia 19% and gastroenteritis (9.4%). 98% (531/541) were cured at D14 in the Almanach arm and 99.6% (519/521) in controls. Rate of secondary hospitalization was 0.2% in each. One death occurred in controls. None of the complications was due to withdrawal of antibiotics or antimalarials at day 0. Rate of antibiotic use was 19% in the Almanach arm and 84% in controls.Conclusion Evidence suggests that the new algorithm, primarily aimed at the rational use of drugs, is as safe as standard practice and leads to a drastic reduction of antibiotic use. The Almanach is currently being tested for clinician adherence to proposed procedures when used on paper or a mobile phone

Cultural events as tourism supply in coastal Catalan resorts

During the last three decades, the number of tourism events has been growing in Catalan coastal resorts because of the recover of Catalan cultural traditions, festivals and folklore, and also because of tourism growth. Catalan tourism resorts use events as catalysers for new supply and as a mean to differentiate and singularize themselves from their competitors. The tourism potential of cultural events is undeniable but there are some problems that prevent a more effective impact as economic and regional development agents. This paper reflects some discussions and conclusions obtained from the analysis of 264 valid responses of a survey made to different Catalan event organizers in 2008 and 2009. We describe and characterize cultural event supply in coastal resorts in order to study the events tourism importance, their capacity to generate and spread economic development, and their managerial model. The analysis is made in a geographical basis, comparing the results of the territorial organization of events of the city of Barcelona, coastal and inland municipalities. Finally some considerations about event regional tourism policy and tourism development are discussed.

Glut2-dependent glucose-sensing controls thermoregulation by enhancing the leptin sensitivity of NPY and POMC neurons.

The physiological contribution of glucose in thermoregulation is not completely established nor whether this control may involve a regulation of the melanocortin pathway. Here, we assessed thermoregulation and leptin sensitivity of hypothalamic arcuate neurons in mice with inactivation of glucose transporter type 2 (Glut2)-dependent glucose sensing. Mice with inactivation of Glut2-dependent glucose sensors are cold intolerant and show increased susceptibility to food deprivation-induced torpor and abnormal hypothermic response to intracerebroventricular administration of 2-deoxy-d-glucose compared to control mice. This is associated with a defect in regulated expression of brown adipose tissue uncoupling protein I and iodothyronine deiodinase II and with a decreased leptin sensitivity of neuropeptide Y (NPY) and proopiomelanocortin (POMC) neurons, as observed during the unfed-to-refed transition or following i.p. leptin injection. Sites of central Glut-2 expression were identified by a genetic tagging approach and revealed that glucose-sensitive neurons were present in the lateral hypothalamus, the dorsal vagal complex, and the basal medulla but not in the arcuate nucleus. NPY and POMC neurons were, however, connected to nerve terminals from Glut2-expressing neurons. Thus, our data suggest that glucose controls thermoregulation and the leptin sensitivity of NPY and POMC neurons through activation of Glut2-dependent glucose-sensing neurons located outside of the arcuate nucleus.

Growth of Crassostrea gasar cultured in marine and estuary environments in Brazilian waters

The objective of this work was to evaluate the growth of the mangrove oyster Crassostrea gasar cultured in marine and estuarine environments. Oysters were cultured for 11 months in a longline system in two study sites - São Francisco do Sul and Florianópolis -, in the state of Santa Catarina, Southern Brazil. Water chlorophyll-α concentration, temperature, and salinity were measured weekly. The oysters were measured monthly (shell size and weight gain) to assess growth. At the end of the culture period, the average wet flesh weight, dry flesh weight, and shell weight were determined, as well as the distribution of oysters per size class. Six nonlinear models (logistic, exponential, Gompertz, Brody, Richards, and Von Bertalanffy) were adjusted to the oyster growth data set. Final mean shell sizes were higher in São Francisco do Sul than in Florianópolis. In addition, oysters cultured in São Francisco do Sul were more uniformly distributed in the four size classes than those cultured in Florianópolis. The highest average values of wet flesh weight and shell weight were observed in São Francisco do Sul, whereas dry flesh weight did not differ between the sites. The estuary environment is more promising for the cultivation of oysters.