Avaliação ultra-sonográfica do osso nasal fetal: evolução das medidas ao longo da gestação

OBJETIVO: além da ausência ultra-sonográfica do osso nasal fetal, sua hipoplasia também apresenta forte associação com a trissomia 21, porém por não haver clara definição do que seja tal hipoplasia, objetivou-se estabelecer seus valores de referência ao longo da gestação, em população brasileira. MÉTODOS: este estudo seccional se baseou em 625 dentre 902 fetos, entre 10 e 39 semanas, considerando-se uma medida de cada indivíduo. Foram excluídos os malformados e aqueles cujas mães apresentavam doenças que, sabidamente, interferem em seu crescimento. Utilizou-se a imagem ecográfica do perfil fetal, com feixe acústico incidindo em ângulo de 45 ou 135° em relação ao plano da face. A média de cada idade gestacional foi estimada pela regressão polinomial. O teste de Anderson-Darling verificou a distribuição normal das medidas (p>0,05). RESULTADOS: dos 625 fetos, 88,3% originaram-se de gestações simples e 11,7% de gestações múltiplas. O avanço da idade gestacional implicou aumento da medida do osso nasal e aumento de sua variabilidade. Encontrou-se tamanho mínimo de 1,0 mm e 4,7 mm no primeiro e segundo trimestres, respectivamente. CONCLUSÕES: há correlação direta entre o tamanho do osso nasal e a idade gestacional. Essa correlação é válida tanto para gestação simples quanto para múltipla. Este trabalho permite adotar a avaliação ecográfica do osso nasal fetal como marcador de cromossomopatias, ao estabelecer os valores de referência de sua medida ao longo da gestação, útil para a população brasileira, com grande miscigenação étnica. Entretanto, necessita-se aprimorar a sistematização e padronização do estudo ecográfico do osso nasal fetal, além de estabelecer seu real valor em fetos previamente classificados como de alto e baixo risco para aneuploidias.

Síndrome do abscesso pituitário em bezerros associada ao uso de tabuleta nasal para desmame interrompido

Descrevem-se surtos e casos esporádicos de síndrome do abscesso pituitário em bovinos no Estado do Rio Grande do Sul. A doença ocorreu em 8 propriedades de gado de corte, nos municípios de Cachoeira do Sul, Lavras do Sul, Bagé, Osório e Vila Nova do Sul, no período de 1998 a 2002. De um total de 2.438 bezerros submetidos ao desmame interrompido com o uso da tabuleta nasal, aproximadamente 35 (1,4%) animais adoeceram e 24 (0,98%) morreram. A idade dos bezerros afetados variava entre 3 e 12 meses. Os animais doentes apresentavam corrimento nasal, depressão, febre, incoordenação motora, andar em círculos, desvio lateral da cabeça, hipermetria, exoftalmia, disfagia, mandíbula caída, protusão lingual, dificuldade de mastigação e sialorréia. Em alguns casos, observou-se também cegueira, acompanhada ou não de turvação dos humores do globo ocular, exoftalmia e opacidade da córnea. Nas fases terminais, ocorriam decúbito lateral, convulsões, nistagmo, opistótono, coma e morte. Os principais achados de necropsia consistiam em abscessos únicos pituitários ou parapituitários que comprimiam dorsalmente o tronco encefálico e nervos cranianos próximos à pituitária. Em alguns casos, havia osteomielite envolvendo o osso baso-esfenóide com a formação de abscessos na substância encefálica, leptomeningite na superfície ventral do encéfalo e medula espinhal cervical e rinite necrosante ou abscedativa associada às lesões traumáticas provocadas pela colocação da tabuleta nasal. Histologicamente, os abscessos correspondiam a grandes agregados de neutrófilos e restos celulares circundados por células mononucleares e proliferação de tecido conjuntivo. Meningite fibrinopurulenta nas leptomeninges do cerebelo, tronco encefálico e medula espinhal cervical também foi observada. Em alguns casos, a inflamação purulenta se estendia para o parênquima da pituitária. Arcanobacterium (Actinomyces) pyogenes foi isolado dos abscessos. O diagnóstico de síndrome do abscesso pituitário foi baseado nos dados epidemiológicos, sinais clínicos, achados macroscópicos, histológicos e microbiológicos.

Mannheimiose pulmonar experimental em bezerros: swab nasal e nasofaringeano como auxílio diagnóstico

Um modelo experimental de mannheimiosepneumônica bovina (MPB) foi utilizado com o objetivo de avaliar as espécies bacterianas das cavidades nasais e nasofaringeanas em diferentes momentos do curso da doença, bem como verificar a eficiência diagnóstica do exame microbiológico dos swabs nasais (SN) e nasofaringeanos (SNF). Um total de 28 bezerros foi distribuído aleatoriamente em quatro grupos experimentais (G1 a G4). SN e SNF foram colhidos sete dias antes e 12 (G1), 24 (G2), 48 (G3) e 72 (G4) horas após a inoculação intrabronquial de Mannheimia haemolytica. Após a indução da MPB, a bactéria M. haemolytica biotipo A foi predominante nos SN e SNF, sendo isolada em todos os momentos avaliados, com exceção de um SN colhido 24 horas após a indução da infecção. Não houve diferença significativa nas taxas de isolamento de Pasteurella multocida nos SN ou SNF, colhidos antes e após a indução da MPB. Contudo, esta bactéria passou a ser isolada mais freqüentemente após a indução da MPB, principalmente no SNF. Portanto, pode-se concluir que o exame microbiológico de SN e SNF é um teste auxiliar no diagnóstico da MPB.

Doenças da cavidade nasal em ruminantes no Brasil

Este trabalho descreve as doenças das fossas nasais diagnosticadas em ruminantes no Hospital Veterinário da Universidade Federal de Campina Grande, em Patos, Paraíba, nos anos de 2003-2009. No período foram registrados três diagnósticos de doenças das fossas nasais de bovinos, três em caprinos e nove em ovinos (de um total de 404 diagnósticos em bovinos, 330 em caprinos e 338 em ovinos). Descrevem-se um caso de rinite atópica em bovinos, sete surtos de conidiobolomicose e dois de pitiose rinofacial em ovinos, dois casos de prototecose e um de aspergilose nasal em caprinos e um mixoma e um fibrossarcoma em bovinos. Adicionalmente, é realizada uma revisão de outras doenças das fossas nasais de ruminantes descritas em outras regiões do Brasil, incluindo oestrose, rinosporidiose, carcinoma epidermóide e tumor etmoidal enzoótico.

Scaling up stepwise feature introduction to construction of large software systems

Developing software is a difficult and error-prone activity. Furthermore, the complexity of modern computer applications is significant. Hence,an organised approach to software construction is crucial. Stepwise Feature Introduction – created by R.-J. Back – is a development paradigm, in which software is constructed by adding functionality in small increments. The resulting code has an organised, layered structure and can be easily reused. Moreover, the interaction with the users of the software and the correctness concerns are essential elements of the development process, contributing to high quality and functionality of the final product. The paradigm of Stepwise Feature Introduction has been successfully applied in an academic environment, to a number of small-scale developments. The thesis examines the paradigm and its suitability to construction of large and complex software systems by focusing on the development of two software systems of significant complexity. Throughout the thesis we propose a number of improvements and modifications that should be applied to the paradigm when developing or reengineering large and complex software systems. The discussion in the thesis covers various aspects of software development that relate to Stepwise Feature Introduction. More specifically, we evaluate the paradigm based on the common practices of object-oriented programming and design and agile development methodologies. We also outline the strategy to testing systems built with the paradigm of Stepwise Feature Introduction.

Doenças da cavidade nasal em pequenos ruminantes no Distrito Federal e no Estado de Goiás

Resumo As enfermidades que acometem a cavidade nasal de pequenos ruminantes podem causar prejuízos aos rebanhos de ovinos e caprinos na região central do Brasil. Foi realizado estudo retrospectivo dos laudos de necropsia do Laboratório de Patologia Veterinária da Universidade de Brasília (LPV-UnB) nos anos de 2003 a 2014 para verificar a ocorrência das doenças que acometeram a cavidade nasal de pequenos ruminantes. Foram analisados 463 protocolos de ovinos e 75 de caprinos totalizando 538 casos. Seis ovinos (6/463 1,29%) foram necropsiados com rinite granulomatosa micótica ou oomicótica e 22 animais do estudo (22/538; 4,08%) tiveram o diagnóstico de oestrose, sendo 86,36% ovinos e 13,64% caprinos. As rinites piogranulomatosas em ovinos ocorreram em áreas alagadas, com abundante material vegetal em decomposição. Os ovinos com pitiose rinofacial apresentaram como principais alterações aumento de volume na região nasal devido a extensas lesões granulomatosas associadas a necrose tecidual, caracterizadas por inúmeros macrófagos e polimorfonucleares circundando centros necróticos contendo o agente envolto por reação de Splendore-Hoeppli. Os ovinos com conidiobolomicose exibiram extensas áreas de necrose e inflamação piogranulomatosa, associadas à presença de hifas fúngicas na nasofaringe e também na região peribulbar e exoftalmia. A maioria dos animais com oestrose não apresentou alterações clínico-patológicas significativas, apesar de serem encontradas larvas principalmente nos seios e conchas nasais, traqueia e seio paranasal. A importância dessas enfermidades ainda é pouco conhecida na região, sendo de grande relevância que as condições clínico-patológicas e epidemiológicas sejam elucidadas para o diagnóstico, o controle e a prevenção, para evitar a expansão e prejuízos para os rebanhos.

A feature-based object-oriented expert system to model and support product design

In this paper a computer program to model and support product design is presented. The product is represented through a hierarchical structure that allows the user to navigate across the product’s components, and it aims at facilitating each step of the detail design process. A graphical interface was also developed, which shows visually to the user the contents of the product structure. Features are used as building blocks for the parts that compose the product, and object-oriented methodology was used as a means to implement the product structure. Finally, an expert system was also implemented, whose knowledge base rules help the user design a product that meets design and manufacturing requirements.

Amplification of 9q34 in childhood adrenocortical tumors: a specific feature unrelated to ethnic origin or living conditions

Adrenocortical tumors (ACT) in children under 15 years of age exhibit some clinical and biological features distinct from ACT in adults. Cell proliferation, hypertrophy and cell death in adrenal cortex during the last months of gestation and the immediate postnatal period seem to be critical for the origin of ACT in children. Studies with large numbers of patients with childhood ACT have indicated a median age at diagnosis of about 4 years. In our institution, the median age was 3 years and 5 months, while the median age for first signs and symptoms was 2 years and 5 months (N = 72). Using the comparative genomic hybridization technique, we have reported a high frequency of 9q34 amplification in adenomas and carcinomas. This finding has been confirmed more recently by investigators in England. The lower socioeconomic status, the distinctive ethnic groups and all the regional differences in Southern Brazil in relation to patients in England indicate that these differences are not important to determine 9q34 amplification. Candidate amplified genes mapped to this locus are currently being investigated and Southern blot results obtained so far have discarded amplification of the abl oncogene. Amplification of 9q34 has not been found to be related to tumor size, staging, or malignant histopathological features, nor does it seem to be responsible for the higher incidence of ACT observed in Southern Brazil, but could be related to an ACT from embryonic origin.

Operant serial feature-positive conditional discrimination with composite features and different topography responses

In a serial feature-positive conditional discrimination procedure the properties of a target stimulus A are defined by the presence or not of a feature stimulus X preceding it. In the present experiment, composite features preceded targets associated with two different topography operant responses (right and left bar pressing); matching and non-matching-to-sample arrangements were also used. Five water-deprived Wistar rats were trained in 6 different trials: X-R®Ar and X-L®Al, in which X and A were same modality visual stimuli and the reinforcement was contingent to pressing either the right (r) or left (l) bar that had the light on during the feature (matching-to-sample); Y-R®Bl and Y-L®Br, in which Y and B were same modality auditory stimuli and the reinforcement was contingent to pressing the bar that had the light off during the feature (non-matching-to-sample); A- and B- alone. After 100 training sessions, the animals were submitted to transfer tests with the targets used plus a new one (auditory click). Average percentages of stimuli with a response were measured. Acquisition occurred completely only for Y-L®Br+; however, complex associations were established along training. Transfer was not complete during the tests since concurrent effects of extinction and response generalization also occurred. Results suggest the use of both simple conditioning and configurational strategies, favoring the most recent theories of conditional discrimination learning. The implications of the use of complex arrangements for discussing these theories are considered.

Nasal CPAP in the delivery room for newborns with extremely low birth weight in a hospital in a developing country

The objective of this study was to determine the feasibility of the use of continuous positive airway pressure installed prophylactically in the delivery room (DR-CPAP), for infants with a birth weight between 500 and 1000 g in settings with limited resources. During 23 months, infants with a birth weight between 500 and 1000 g consecutively received DR-CPAP. A total of 33 infants with low birth weight were enrolled, 16 (48.5%) were females. Only 14 (42.4%) received antenatal corticosteroids and only 2 of those 14 (14.3%) infants weighing 500-750 g were not intubated in the delivery room, and apnea was given as the reason for intubation of these patients. Of the 19 infants in the 751-1000 g weight range, 9 (47.4%) were intubated in the delivery room, 6 due to apnea and 3 due to respiratory discomfort. For DR-CPAP to be successful, it is probably necessary for preterm babies to be more prepared at birth to withstand the respiratory effort without the need for intubation. Antenatal corticosteroids and better prenatal monitoring are fundamental for success of DR-CPAP.

Scalable Feature Selection Applications for Genome-Wide Association Studies of Complex Diseases

Personalized medicine will revolutionize our capabilities to combat disease. Working toward this goal, a fundamental task is the deciphering of geneticvariants that are predictive of complex diseases. Modern studies, in the formof genome-wide association studies (GWAS) have afforded researchers with the opportunity to reveal new genotype-phenotype relationships through the extensive scanning of genetic variants. These studies typically contain over half a million genetic features for thousands of individuals. Examining this with methods other than univariate statistics is a challenging task requiring advanced algorithms that are scalable to the genome-wide level. In the future, next-generation sequencing studies (NGS) will contain an even larger number of common and rare variants. Machine learning-based feature selection algorithms have been shown to have the ability to effectively create predictive models for various genotype-phenotype relationships. This work explores the problem of selecting genetic variant subsets that are the most predictive of complex disease phenotypes through various feature selection methodologies, including filter, wrapper and embedded algorithms. The examined machine learning algorithms were demonstrated to not only be effective at predicting the disease phenotypes, but also doing so efficiently through the use of computational shortcuts. While much of the work was able to be run on high-end desktops, some work was further extended so that it could be implemented on parallel computers helping to assure that they will also scale to the NGS data sets. Further, these studies analyzed the relationships between various feature selection methods and demonstrated the need for careful testing when selecting an algorithm. It was shown that there is no universally optimal algorithm for variant selection in GWAS, but rather methodologies need to be selected based on the desired outcome, such as the number of features to be included in the prediction model. It was also demonstrated that without proper model validation, for example using nested cross-validation, the models can result in overly-optimistic prediction accuracies and decreased generalization ability. It is through the implementation and application of machine learning methods that one can extract predictive genotype–phenotype relationships and biological insights from genetic data sets.

Partikkelikokojakaumamenetelmän testaus INCA Feature

Tässä työssä testattiin partikkelikokojakaumien analysoinnissa käytettävää kuvankäsittelyohjelmaa INCA Feature. Partikkelikokojakaumat määritettiin elektronimikroskooppikuvista INCA Feature ohjelmaa käyttäen partikkeleiden projektiokuvista päällystyspigmenttinä käytettävälle talkille ja kahdelle eri karbonaattilaadulle. Lisäksi määritettiin partikkelikokojakaumat suodatuksessa ja puhdistuksessa apuaineina käytettäville piidioksidi- ja alumiinioksidihiukkasille. Kuvankäsittelyohjelmalla määritettyjä partikkelikokojakaumia verrattiin partikkelin laskeutumisnopeuteen eli sedimentaatioon perustuvalla SediGraph 5100 analysaattorilla ja laserdiffraktioon perustuvalla Coulter LS 230 menetelmällä analysoituihin partikkelikokojakaumiin. SediGraph 5100 ja kuva-analyysiohjelma antoivat talkkipartikkelien kokojakaumalle hyvin samankaltaisen keskiarvon. Sen sijaan Coulter LS 230 laitteen antama kokojakauman keskiarvo poikkesi edellisistä. Kaikki vertailussa olleet partikkelikokojakaumamenetelmät asettivat eri näytteiden partikkelit samaan kokojärjestykseen. Kuitenkaan menetelmien tuloksia ei voida numeerisesti verrata toisiinsa, sillä kaikissa käytetyissä analyysimenetelmissä partikkelikoon mittaus perustuu partikkelin eri ominaisuuteen. Työn perusteella kaikki testatut analyysimenetelmät soveltuvat paperipigmenttien partikkelikokojakaumien määrittämiseen. Tässä työssä selvitettiin myös kuva-analyysiin tarvittava partikkelien lukumäärä, jolla analyysitulos on luotettava. Työssä todettiin, että analysoitavien partikkelien lukumäärän tulee olla vähintään 300 partikkelia. Liian suuri näytemäärä lisää kokojakauman hajontaa ja pidentää analyysiin käytettyä aikaa useaan tuntiin. Näytteenkäsittely vaatii vielä lisää tutkimuksia, sillä se on tärkein ja kriittisin vaihe SEM ja kuva-analyysiohjelmalla tehtävää partikkelikokoanalyysiä. Automaattisten mikroskooppien yleistyminen helpottaa ja nopeuttaa analyysien tekoa, jolloin menetelmän suosio tulee kasvamaan myös paperipigmenttien tutkimuksessa. Laitteiden korkea hinta ja käyttäjältä vaadittava eritysosaaminen tulevat rajaamaan käytön ainakin toistaiseksi tutkimuslaitoksiin.

Evolutionary synthesis of stochastic gene network models using feature-based search spaces

A feature-based fitness function is applied in a genetic programming system to synthesize stochastic gene regulatory network models whose behaviour is defined by a time course of protein expression levels. Typically, when targeting time series data, the fitness function is based on a sum-of-errors involving the values of the fluctuating signal. While this approach is successful in many instances, its performance can deteriorate in the presence of noise. This thesis explores a fitness measure determined from a set of statistical features characterizing the time series' sequence of values, rather than the actual values themselves. Through a series of experiments involving symbolic regression with added noise and gene regulatory network models based on the stochastic 'if-calculus, it is shown to successfully target oscillating and non-oscillating signals. This practical and versatile fitness function offers an alternate approach, worthy of consideration for use in algorithms that evaluate noisy or stochastic behaviour.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.