Fitoplâncton (exceto Chlorophyceae) de um lago artificial urbano no Sul do Brasil

O presente estudo tem como objetivo conhecer a composição do fitoplâncton no Lago das Tartarugas, situado no Jardim Botânico da cidade de Porto Alegre, Estado do Rio Grande do Sul. As amostragens foram realizadas mensalmente, no período de junho de 2007 a maio de 2008, em uma estação em três diferentes níveis de profundidade, na zona pelágica. Um total de 49 táxons específicos e infraespecíficos pertencentes a sete classes foram registrados. Cyanobacteria apresentou maior número de táxons (35% dos táxons identificados) seguida de Bacillariophyceae (33%) e Euglenophyceae (16,3%). São apresentadas descrições, medidas e ilustrações dos táxons, assim como a distribuição dos mesmos durante o ciclo anual.

Cianobactérias planctônicas de um lago artificial urbano na cidade de Goiânia, GO

Os criatórios de peixe do estado de Goiás são inúmeros e de intensa atividade recreativa. No entanto, estudos sobre as cianobactérias nesses ambientes são escassos, fato preocupante, uma vez que é comum notar-se intensa proliferação do fitoplâncton em pesqueiros, principalmente devido a ações antrópicas. O perigo consiste na formação de florações de espécies potencialmente tóxicas, principalmente de cianobactérias. Este trabalho visa inventariar as espécies planctônicas de cianobactérias ocorrentes em um pesqueiro (lago Jaó - um lago artificial raso) da área municipal de Goiânia (GO) (16º39'13" S-49º13'26" O). As amostragens foram realizadas nos períodos de seca (2003 a 2008) e chuva (2009), quando visualmente era evidente a ocorrência de florações. Foram aferidas variáveis climatológicas, morfométricas e limnológicas. O período de seca foi representativo nos anos amostrados apresentando no máximo 50 mm de precipitação mensal em 2005. Foram registrados 31 táxons de cianobactérias pertencentes aos gêneros Dolichospermum (5 spp.), Aphanocapsa (4 spp.), Microcystis (3 spp.), Pseudanabaena (3 spp.), Radiocystis (2 spp.), Oscillatoria (2 spp.), Bacularia, Coelosphaerium, Cylindrospermopsis, Geitlerinema, Glaucospira, Limnothrix, Pannus, Phormidium, Planktolyngbya, Planktothrix, Sphaerocavum e Synechocystis, esses últimos com uma espécie cada. Nos anos de 2003 a 2005 ocorreu predomínio de florações de espécies de Dolichospermum e em 2006 predominaram espécies de Microcystis, Radiocystis e Aphanocapsa. Das espécies inventariadas neste estudo, 21 são primeiras citações para o estado de Goiás e 13 foram constadas na literatura como potencialmente tóxicas.

Plant height reduction in populations of triticale (X triticosecale Wittmack) by induced mutations and artificial crosses

Induced mutations by gamma radiation (0, 5, 10, 20 and 40 kR doses) and reciprocal crosses were tested as mechanisms of enhancing genetic variability for plant height in two triticale cultivars, BR4 and EMBRAPA18. The reciprocal crosses and all doses of radiation showed similar increase in genetic amplitude for this trait, being suitable for increasing variability in breeding programs. Genotypes showed different responses as the gamma ray doses were increased, expressing shorter plant height. The decision of using induced mutations or artificial crosses depends on the resources available and the selection method to be used

Dynamic Analysis Model of Spherical Roller Bearings with Defects

Rolling element bearings are essential components of rotating machinery. The spherical roller bearing (SRB) is one variant seeing increasing use, because it is self-aligning and can support high loads. It is becoming increasingly important to understand how the SRB responds dynamically under a variety of conditions. This doctoral dissertation introduces a computationally efficient, three-degree-of-freedom, SRB model that was developed to predict the transient dynamic behaviors of a rotor-SRB system. In the model, bearing forces and deflections were calculated as a function of contact deformation and bearing geometry parameters according to nonlinear Hertzian contact theory. The results reveal how some of the more important parameters; such as diametral clearance, the number of rollers, and osculation number; influence ultimate bearing performance. Distributed defects, such as the waviness of the inner and outer ring, and localized defects, such as inner and outer ring defects, are taken into consideration in the proposed model. Simulation results were verified with results obtained by applying the formula for the spherical roller bearing radial deflection and the commercial bearing analysis software. Following model verification, a numerical simulation was carried out successfully for a full rotor-bearing system to demonstrate the application of this newly developed SRB model in a typical real world analysis. Accuracy of the model was verified by comparing measured to predicted behaviors for equivalent systems.

Protein defects in neuromuscular diseases

Muscular dystrophies are a heterogeneous group of genetically determined progressive disorders of the muscle with a primary or predominant involvement of the pelvic or shoulder girdle musculature. The clinical course is highly variable, ranging from severe congenital forms with rapid progression to milder forms with later onset and a slower course. In recent years, several proteins from the sarcolemmal muscle membrane (dystrophin, sarcoglycans, dysferlin, caveolin-3), from the extracellular matrix (alpha2-laminin, collagen VI), from the sarcomere (telethonin, myotilin, titin, nebulin), from the muscle cytosol (calpain 3, TRIM32), from the nucleus (emerin, lamin A/C, survival motor neuron protein), and from the glycosylation pathway (fukutin, fukutin-related protein) have been identified. Mutations in their respective genes are responsible for different forms of neuromuscular diseases. Protein analysis using Western blotting or immunohistochemistry with specific antibodies is of the utmost importance for the differential diagnosis and elucidation of the physiopathology of each genetic disorder involved. Recent molecular studies have shown clinical inter- and intra-familial variability in several genetic disorders highlighting the importance of other factors in determining phenotypic expression and the role of possible modifying genes and protein interactions. Developmental studies can help elucidate the mechanism of normal muscle formation and thus muscle regeneration. In the last fifteen years, our research has focused on muscle protein expression, localization and possible interactions in patients affected by different forms of muscular dystrophies. The main objective of this review is to summarize the most recent findings in the field and our own contribution.

Congenital upper limb defects in Finland 1993-2005

Background: Interest in limb defects has grown after the thalidomide tragedy in the 1960s. As a result, congenital malformation registries, monitoring changes in birthprevalence and defect patterns, have been established in several countries. However, there are only a few true population based studies on birth prevalence of upper limb defects. The burden of hospital care among these children, specifically in terms of the number of admissions and total time spent in hospital, is also unknown. Aims and Methods: This study is based on information gathered from the Finnish Register of Congenital malformations (FRM) and the Finnish Hospital Discharge Register (FHDR). A total of 417 children born between 1993 and 2005 with an upper limb defect were gathered from the FRM. The upper limb defects were classified using the International Federation of Societies for Surgery of the Hand -classification that enables comparison with previous and future studies. Birth and live birth prevalence, sex and side distribution, frequency of associated anomalies as well as the proportion of perinatal and infant deaths according to the different subtypes were calculated. The number of hospital admissions, days spent in hospital, number and type of surgical operations were collected from the FHDR. Special features of two subgroups, radial ray defects (RRD) and constriction band syndrome (CBS), were explored. Results: Upper limb defects were observed in 417 of 753 342 consecutive births and in 392 of 750 461 live births. Birth prevalence was 5.5 per 10 000 births and 5.2 per 10 000 live births. Multiple anomalies or a known syndrome was found in 250 cases (60%). Perinatal mortality was 139 per 1000 births and infant mortality 135 per 1000 live births (overall Finnish perinatal mortality <5 per 1000 births and infant mortality 3.7 per 1000 live births). Altogether, 138 infants had RRD and 120 (87%) of these had either a known syndrome or multiple major anomalies. The proportion of perinatal deaths in RRD group was 29% (40/138) and infant deaths 35% (43/123). Fifty-one children had CBS in upper limbs. Fifteen of these (29%) had other major anomalies associated with constriction rings. The number of hospital admissions per year of children with congenital upper limb defects was 11-fold and the time spent in hospital 13-fold as compared with the general paediatric population. Conclusions: Birth prevalence of congenital upper limb defects was 5.5 per 10 000 births and 5.2 per 10 000 live births. RRD was especially associated with other major anomalies and high mortality. Nearly one third of the children with CBS also had other major anomalies suggesting different aetiologies inside the group. The annual burden of hospital care of children with congenital upper limb defects was at least 11-fold as compared with the general paediatric population.

Automated grading of left ventricular segmental wall motion by an artificial neural network using color kinesis images

The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images. An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global and regional WM in real time. We evaluated 21 normal subjects and 20 patients with LVWM abnormalities revealed by two-dimensional echocardiography. CK images were obtained in two sets of viewing planes. A method was developed to analyze CK images, providing quantitation of fractional area change in each of the 16 LV segments. Two experienced observers analyzed LVWM from two-dimensional images and scored them as: 1) normal, 2) mild hypokinesia, 3) moderate hypokinesia, 4) severe hypokinesia, 5) akinesia, and 6) dyskinesia. Based on expert analysis of 10 normal subjects and 10 patients, we trained a multilayer perceptron ANN using a back-propagation algorithm to provide automated grading of LVWM, and this ANN was then tested in the remaining subjects. Excellent concordance between expert and ANN analysis was shown by ROC curve analysis, with measured area under the curve of 0.975. An excellent correlation was also obtained for global LV segmental WM index by expert and ANN analysis (R² = 0.99). In conclusion, ANN showed high accuracy for automated semi-quantitative grading of WM based on CK images. This technique can be an important aid, improving diagnostic accuracy and reducing inter-observer variability in scoring segmental LVWM.

Congenital ventricular septal defects and prenatal exposure to cyclooxygenase inhibitors

Ventricular septal defects (VSDs) are common congenital abnormalities which have been reported to be associated with maternal fever and various environmental factors. The aim of the present study was to evaluate the effect of prenatal exposure to cyclooxygenase (COX) inhibitors on heart defects. A retrospective statistical analysis was performed using data collected in our laboratory during various teratological studies carried out on albino CRL:(WI)WUBR Wistar strain rats from 1997 to 2004. The observations were compared with concurrent and historic control data, as well as findings from other developmental toxicological studies with selective and nonselective COX-2 inhibitors. Despite the lack of significant differences in the frequency of VSDs between drug-exposed and control groups, statistical analysis by the two-sided Mantel-Haenszel test and historical control data showed a higher incidence of heart defects in offspring exposed to nonselective COX inhibitors (30.06/10,000). Unlike other specific inhibitors, aspirin (46.26/10,000) and ibuprofen (106.95/10,000) significantly increased the incidence of the VSD when compared with various control groups (5.38-19.72/10,000). No significant differences in length or weight were detected between fetuses exposed to COX inhibitors and born with VSD and non-malformed offsprings. However, a statistically significant increase of fetal body length and decrease of body mass index were found in fetuses exposed to COX inhibitors when compared with untreated control. We conclude that prenatal exposure to COX inhibitors, especially aspirin and ibuprofen, increased the incidence of VSDs in rat offspring but was not related to fetal growth retardation.

Artificial reflecting structures based on metamaterials

This thesis studies metamaterial-inspired mirrors which provide the most general control over the amplitude and phase of the reflected wavefront. The goal is to explore practical possibilities in designing fully reflective electromagnetic structures with full control over reflection phase. The first part of the thesis describes a planar focusing metamirror with the focal distance less than the operating wavelength. Its practical applicability from the viewpoint of aberrations when the incident angle deviates from the normal one is verified numerically and experimentally. The results indicate that the proposed focusing metamirror can be efficiently employed in many different applications due to its advantages over other conventional mirrors. In the second part of the thesis a new theoretical concept of reflecting metasurface operation is introduced based on Huygens’ principle. This concept in contrast to known approaches takes into account all the requirements of perfect metamirror operation. The theory shows a route to improve the previously proposed metamirrors through tilting the individual inclusions of the structure at a chosen angle from normal. It is numerically tested and the results demonstrate improvements over the previous design.

Synergistic control of forearm based on accelerometer data and artificial neural networks

In the present study, we modeled a reaching task as a two-link mechanism. The upper arm and forearm motion trajectories during vertical arm movements were estimated from the measured angular accelerations with dual-axis accelerometers. A data set of reaching synergies from able-bodied individuals was used to train a radial basis function artificial neural network with upper arm/forearm tangential angular accelerations. The trained radial basis function artificial neural network for the specific movements predicted forearm motion from new upper arm trajectories with high correlation (mean, 0.9149-0.941). For all other movements, prediction was low (range, 0.0316-0.8302). Results suggest that the proposed algorithm is successful in generalization over similar motions and subjects. Such networks may be used as a high-level controller that could predict forearm kinematics from voluntary movements of the upper arm. This methodology is suitable for restoring the upper limb functions of individuals with motor disabilities of the forearm, but not of the upper arm. The developed control paradigm is applicable to upper-limb orthotic systems employing functional electrical stimulation. The proposed approach is of great significance particularly for humans with spinal cord injuries in a free-living environment. The implication of a measurement system with dual-axis accelerometers, developed for this study, is further seen in the evaluation of movement during the course of rehabilitation. For this purpose, training-related changes in synergies apparent from movement kinematics during rehabilitation would characterize the extent and the course of recovery. As such, a simple system using this methodology is of particular importance for stroke patients. The results underlie the important issue of upper-limb coordination.

Proteoliposomes as matrix vesicles' biomimetics to study the initiation of skeletal mineralization

During the process of endochondral bone formation, chondrocytes and osteoblasts mineralize their extracellular matrix by promoting the formation of hydroxyapatite (HA) seed crystals in the sheltered interior of membrane-limited matrix vesicles (MVs). Ion transporters control the availability of phosphate and calcium needed for HA deposition. The lipidic microenvironment in which MV-associated enzymes and transporters function plays a crucial physiological role and must be taken into account when attempting to elucidate their interplay during the initiation of biomineralization. In this short mini-review, we discuss the potential use of proteoliposome systems as chondrocyte- and osteoblast-derived MVs biomimetics, as a means of reconstituting a phospholipid microenvironment in a manner that recapitulates the native functional MV microenvironment. Such a system can be used to elucidate the interplay of MV enzymes during catalysis of biomineralization substrates and in modulating in vitro calcification. As such, the enzymatic defects associated with disease-causing mutations in MV enzymes could be studied in an artificial vesicular environment that better mimics their in vivo biological milieu. These artificial systems could also be used for the screening of small molecule compounds able to modulate the activity of MV enzymes for potential therapeutic uses. Such a nanovesicular system could also prove useful for the repair/treatment of craniofacial and other skeletal defects and to facilitate the mineralization of titanium-based tooth implants.

Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

Previsão de estabilidade de óleos vegetais através da rede de inteligência artificial

Redes Neurais Artificiais são técnicas computacionais que se utilizam de um modelo matemático capaz de adquirir conhecimentos pela experiência; esse comportamento inteligente da rede provém das interações entre unidades de processamento, denominadas de neurônios artificiais. O objetivo deste trabalho foi criar uma rede neural capaz de prever a estabilidade de óleos vegetais, a partir de dados de suas composições químicas, visando um modelo para a previsão da shelf-life de óleos vegetais, tendo como parâmetros apenas dados de suas composições químicas. Os primeiros passos do processo de desenvolvimento da rede consistiram na coleta de dados relativos ao problema e sua separação em um conjunto de treinamento e outro de testes. Estes conjuntos apresentaram como variáveis dados de composição química, que incluíram os valores totais em ácidos graxos, fenóis, tocoferóis e a composição individual em ácidos graxos. O passo seguinte foi a execução do treinamento, onde o padrão de entrada apresentado à rede como parâmetro de estabilidade foi o índice de peróxido, determinado experimentalmente por um período de 16 dias de armazenagem na ausência de luz, a 65ºC. Após o treinamento foi testada a capacidade de previsão adquirida pela rede, em função do parâmetro de estabilidade adotado, mas com um novo grupo de óleos. Seguindo o teste, foi determinada a correlação linear entre os valores de estabilidade previstos pela rede e aqueles determinados experimentalmente. Com os resultados obtidos, pode-se confirmar a viabilidade de previsão da estabilidade de óleos vegetais pela rede neural, a partir de dados de sua composição química, utilizando como parâmetro de estabilidade o índice de peróxido.