Allgrove syndrome and motor neuron disease

Allgrove or triple A syndrome (AS or AAA) is a rare autosomal recessive syndrome with variable phenotype due to mutations in AAAS gene which encodes a protein called ALADIN. Generally, it’s characterized by of adrenal insufficiency in consequence of adrenocorticotropic hormone (ACTH) resistance, besides of achalasia, and alacrimia. Neurologic features are varied and have been the subject of several case reports and reviews. A few cases of Allgrove syndrome with motor neuron disease have been already described. A 25-year-old white man, at the age of four, presented slowly progressive distal amyotrophy and weakness, autonomic dysfunction, dysphagia and lack of tears. He suffered later of orthostatic hypotension and erectile dysfunction. He presented distal amytrophy in four limbs, tongue myofasiculations, alacrimia, hoarseness and dysphagia due to achalasia. The ENMG showed generalized denervation with normal conduction velocities. Genetic testing revealed 2 known pathogenic variants in the AAAS gene (c.938T>C and c.1144_1147delTCTG). Our case presented a distal spinal amyotrophy with slow evolution and symptoms and signs of AS with a mutation in AAAS gen. Some cases of motor neuron disease, as ours, may be due to AAS. Early diagnosis is extremely important for symptomatic treatment

DISTRIBUIÇÃO E BIOMASSA DE MACROALGAS EM UM MANGUEZAL DA BAÍA DA BABITONGA, SC: RESULTADOS PRELIMINARES

This work aims to assess distribution and biomass of epiphyte macroalgae of mangrove roots in the Babitonga Bay. The macroalgae were collected monthly in three topographyc levels into the mangrove (Places A, B and C). In each place the collect was stratified in the trees (0 to 10 cm high, 10 to 20 cm , etc). The observed Rhodophyta, from higher to smaller biomass, were: Bostrychia calliptera, Bostrychia pinnata, Bostrychia radicans f. radicans, Bostrychia montagnei, Catenella caespitosa, Caloglossa leprieurii, Bostrychia tenella, Caloglossa ogazawaraensis, Bostrychia radicans f. moniliforme, Bostrychia moritziana, Polysiphonia howei, Bostrychia binderi, Gelidium spp., Polysiphonia tepida. The observed Chlorophyta were: Bloodleopsis pusilla, Cladophoropsis membranacea, Rhizoclonium spp., Ulvaria oxysperma, Enteromorpha spp. There are strong variation on horizontal and vertical biomass and on contribution of each species to total biomass. In the mangrove fringe (place A) the algae occur from 0 to 60 cm high in the trees, the mean biomass along this high varies 30 and 45 g m-2 of substrate. Higher values of biomass occur between 10 and 30 cm high, rising to 75 g m-2. On place B (intermediate tidal flooding) the algae occur from 0 to 30 cm high in the trees, the mean biomass along this high varies 20 and 30 g m-2 of substrate. Higher values of biomass occur between 0 and 10 cm high (50 g m-2 of substrate), but high values may also occur between 10 and 20 cm high. In the inner mangrove (place C) the algae occur from 0 to 20 cm high in the trees, the mean biomass along this high varies 10 and 20 g m-2 of substrate. Like place B, higher values of biomass occur between 0 and 10 cm high (35 g m-2 of substrate), but high values may also occur between 10 and 20 cm high. The green algae, Bloodleopsis pusilla, Cladophoropsis membranacea, Rhizoclonium, and the red algae, Bostrychia montagnei, Caloglossa leprieurii and Caloglossa ogazawaraensis were mainly present from 0 to 10 cm high, and rarely occur above 20 cm. Bostrychia radicans f. radicans presents the most broad distribution, has the higher frequency of occurrence in all places and all strata, and it is the main algae in the upper strata. The higher values of biomass, specially on place A, are due to Bostrychia calliptera and Bostrychia pinnata. This two algae also have a broad vertical and horizontal distribution, but they have higher values from 10 to 30 cm high. The results found until now suggest that macroalgae may be an important component of mangrove primary production. Meanwhile, to evaluate the mangrove magroalgae biomass, we need to include algae epiphytic on pneumatophores. And to evaluate the contribution of these algae to the total primary production of the mangrove, it will be necessary to complement biomass data with ecophysiological experiments, including the responses of growth and photosynthetic rates to environmental factors.Este trabalho tem como objetivo determinar a distribuição e quantificar a biomassa de macroalgas presentes nas raízes e troncos das árvores de manguezal da Baía de Babitonga. Para tal, as macroalgas foram coletadas mensalmente (setembro/1997 a junho/1998) em 3 níveis topográficos dentro do manguezal (Linhas A, B e C). Em cada linha a coleta foi estratificada de acordo com a altura das algas no tronco (0 a 10 cm de altura, 10 a 20 cm , etc). As espécies de Rhodophyta observadas, em ordem decrescente de biomassa, foram: Bostrychia calliptera, Bostrychia pinnata, Bostrychia radicans f. radicans, Bostrychia montagnei, Catenella caespitosa, Caloglossa leprieurii, Bostrychia tenella, Caloglossa ogazawaraensis, Bostrychia radicans f. moniliforme, Bostrychia moritziana, Polysiphonia howei, Bostrychia binderi, Gelidium spp., Polysiphonia tepida. As Chlorophyta são Bloodleopsis pusilla, Cladophoropsis membranacea, Rhizoclonium spp., Ulvaria oxysperma, Enteromorpha spp. Há uma forte variação horizontal e vertical na biomassa e na contribuição de cada espécie para a biomassa total. Na franja do manguezal (linha A) as algas ocupam uma altura de 60 cm, e a biomassa média por tronco varia entre 30 e 45 g m-2 de tronco. A maior biomassa ocorre entre 10 e 30 cm, chegando a 75 g m-2 de tronco. Na porção intermediária (linha B) as algas ocupam uma altura de 30 cm e a biomassa média varia entre 20 e 30 g m-2 de tronco. A biomassa é maior nos primeiros 10 cm (50 g m-2 de tronco), mas pode atingir altos valores também entre 10 e 20 cm. Na porção interna do manguezal (linha C) as algas ocupam uma altura de 20 cm, e a biomassa média varia entre 10 e 20 g m-2 de tronco. Assim como na linha B, a biomassa é maior nos primeiros 10 cm (35 g m-2 de tronco), mas pode atingir altos valores também entre 10 e 20 cm. As algas verdes Bloodleopsis pusilla, Cladophoropsis membranacea, Rhizoclonium, e as algas vermelhas Bostrychia montagnei, Caloglossa leprieurii e Caloglossa ogazawaraensis estão presentes principalmente nos primeiros 10 cm de altura, raramente ocorrendo acima de 20 cm. Bostrychia radicans f. radicans é a alga mais amplamente distribuída, com maior freqüência de ocorrência e a mais abundante na região superior do tronco nas três linhas. As algas que apresentam a maior biomassa, especialmente na linha A, são Bostrychia calliptera e Bostrychia pinnata, que também apresentam distribuição vertical e horizontal ampla, mas são mais abundantes entre 10 e 30 cm de altura. Os resultados obtidos até o momento indicam que as macroalgas podem ser vistas como um componente produtor representativo dentro do manguezal. Entretanto, para uma avaliação da biomassa de macroalgas no manguezal como um todo, é necessário quantificar a biomassa de algas em pneumatóforos. Para avaliar a contribuição destas algas para a produção primária do manguezal, os dados de biomassa devem ser complementados com experimentos de crescimento e produtividade, com relação aos fatores ambientais

Affective recognition from EEG signals: an integrated data-mining approach

Emotions play an important role in human communication, interaction, and decision making processes. Therefore, considerable efforts have been made towards the automatic identification of human emotions, in particular electroencephalogram (EEG) signals and Data Mining (DM) techniques have been then used to create models recognizing the affective states of users. However, most previous works have used clinical grade EEG systems with at least 32 electrodes. These systems are expensive and cumbersome, and therefore unsuitable for usage during normal daily activities. Smaller EEG headsets such as the Emotiv are now available and can be used during daily activities. This paper investigates the accuracy and applicability of previous affective recognition methods on data collected with an Emotiv headset while participants used a personal computer to fulfill several tasks. Several features were extracted from four channels only (AF3, AF4, F3 and F4 in accordance with the 10–20 system). Both Support Vector Machine and Naïve Bayes were used for emotion classification. Results demonstrate that such methods can be used to accurately detect emotions using a small EEG headset during a normal daily activity

Towards emotion recognition for virtual environments: an evaluation of eeg features on benchmark dataset

One of the challenges in virtual environments is the difficulty users have in interacting with these increasingly complex systems. Ultimately, endowing machines with the ability to perceive users emotions will enable a more intuitive and reliable interaction. Consequently, using the electroencephalogram as a bio-signal sensor, the affective state of a user can be modelled and subsequently utilised in order to achieve a system that can recognise and react to the user’s emotions. This paper investigates features extracted from electroencephalogram signals for the purpose of affective state modelling based on Russell’s Circumplex Model. Investigations are presented that aim to provide the foundation for future work in modelling user affect to enhance interaction experience in virtual environments. The DEAP dataset was used within this work, along with a Support Vector Machine and Random Forest, which yielded reasonable classification accuracies for Valence and Arousal using feature vectors based on statistical measurements and band power from the and waves and High Order Crossing of the EEG signal

The relationship between subtypes of depression and cardiovascular disease: a systematic review of biological models

A compelling association has been observed between cardiovascular disease (CVD) and depression, suggesting individuals with depression to be at significantly higher risk for CVD and CVD-related mortality. Systemic immune activation, hypothalamic–pituitary–adrenal (HPA) axis hyperactivity, arterial stiffness and endothelial dysfunction have been frequently implicated in this relationship. Although a differential epidemiological association between CVD and depression subtypes is evident, it has not been determined if this indicates subtype specific biological mechanisms. A comprehensive systematic literature search was conducted using PubMed and PsycINFO databases yielding 147 articles for this review. A complex pattern of systemic immune activation, endothelial dysfunction and HPA axis hyperactivity is suggestive of the biological relationship between CVD and depression subtypes. The findings of this review suggest that diagnostic subtypes rather than a unifying model of depression should be considered when investigating the bidirectional biological relationship between CVD and depression. The suggested model of a subtype-specific biological relationship between depression and CVDs has implications for future research and possibly for diagnostic and therapeutic processes

Spatial analysis of avoidable hospitalizations due to tuberculosis in Ribeirao Preto, SP, Brazil (2006-2012)

ABSTRACT OBJECTIVE To describe the spatial distribution of avoidable hospitalizations due to tuberculosis in the municipality of Ribeirao Preto, SP, Brazil, and to identify spatial and space-time clusters for the risk of occurrence of these events. METHODS This is a descriptive, ecological study that considered the hospitalizations records of the Hospital Information System of residents of Ribeirao Preto, SP, Southeastern Brazil, from 2006 to 2012. Only the cases with recorded addresses were considered for the spatial analyses, and they were also geocoded. We resorted to Kernel density estimation to identify the densest areas, local empirical Bayes rate as the method for smoothing the incidence rates of hospital admissions, and scan statistic for identifying clusters of risk. Softwares ArcGis 10.2, TerraView 4.2.2, and SaTScanTM were used in the analysis. RESULTS We identified 169 hospitalizations due to tuberculosis. Most were of men (n = 134; 79.2%), averagely aged 48 years (SD = 16.2). The predominant clinical form was the pulmonary one, which was confirmed through a microscopic examination of expectorated sputum (n = 66; 39.0%). We geocoded 159 cases (94.0%). We observed a non-random spatial distribution of avoidable hospitalizations due to tuberculosis concentrated in the northern and western regions of the municipality. Through the scan statistic, three spatial clusters for risk of hospitalizations due to tuberculosis were identified, one of them in the northern region of the municipality (relative risk [RR] = 3.4; 95%CI 2.7–4,4); the second in the central region, where there is a prison unit (RR = 28.6; 95%CI 22.4–36.6); and the last one in the southern region, and area of protection for hospitalizations (RR = 0.2; 95%CI 0.2–0.3). We did not identify any space-time clusters. CONCLUSIONS The investigation showed priority areas for the control and surveillance of tuberculosis, as well as the profile of the affected population, which shows important aspects to be considered in terms of management and organization of health care services targeting effectiveness in primary health care