Rates of gene rearrangement and nucleotide substitution are correlated in the mitochondrial genomes of insects

A number of studies indicated that lineages of animals with high rates of mitochondrial (mt) gene rearrangement might have high rates of mt nucleotide substitution. We chose the hemipteroid assemblage and the Insecta to test the idea that rates of mt gene rearrangement and mt nucleotide substitution are correlated. For this purpose, we sequenced the mt genome of a lepidopsocid from the Psocoptera, the only order of hemipteroid insects for which an entire mtDNA sequence is not available. The mt genome of this lepidopsocid is circular, 16,924 bp long, and contains 37 genes and a putative control region; seven tRNA genes and a protein-coding gene in this genome have changed positions relative to the ancestral arrangement of mt genes of insects. We then compared the relative rates of nucleotide substitution among species from each of the four orders of hemipteroid insects and among the 20 insects whose mt genomes have been sequenced entirely. All comparisons among the hernipteroid insects showed that species with higher rates of gene rearrangement also had significantly higher rates of nucleotide substitution statistically than did species with lower rates of gene rearrangement. In comparisons among the 20 insects, where the mt genomes of the two species differed by more than five breakpoints, the more rearranged species always had a significantly higher rate of nucleotide substitution than the less rearranged species. However, in comparisons where the mt genomes of two species differed by five or less breakpoints, the more rearranged species did not always have a significantly higher rate of nucleotide substitution than the less rearranged species. We tested the statistical significance of the correlation between the rates of mt gene rearrangement and mt nucleotide substitution with nine pairs of insects that were phylogenetically independent from one 2 another. We found that the correlation was positive and statistically significant (R-2 = 0.73, P = 0.01; R-s = 0.67, P < 0.05). We propose that increased rates of nucleotide substitution may lead to increased rates of gene rearrangement in the mt genomes of insects.

Primary aldosteronism: From genesis to genetics

The fact that a debate concerning the unexpectedly high prevalence of normokalaemic primary aldosteronism (PAL) attracted a large audience at the 2002 Scientific Meeting of the International Society of Hypertension makes it timely to address this issue. The affirmative case argues that PAL is the most common potentially curable and specifically treatable form of hypertension, itself the most common chronic disorder in Western societies, with significant morbidity and mortality, consuming large proportions of health budgets. Recent discoveries about the genetics of aldosterone production and of its unexpectedly broad effects on the cardiovascular system need to be placed in clinical context.

The genetics of glycosylation in Gram-negative bacteria

In recent years there has been a dramatic increase in reports of glycosylation of proteins in various Gram-negative systems including Neisseria meningitidis, Neisseria gonorrhoeae, Campylobacter jejuni, Pseudomonas aeruginosa, Escherichia coli, Caulobacter crescentus, Aeromonas caviae and Helicobacter pylori. Although this growing list contains many important pathogens (reviewed by Benz and Schmidt [Mol. Microbiol. 45 (2002) 267-276]) and the glycosylations are found on proteins important in pathogenesis such as pili, adhesins and flagella the precise role(s) of the glycosylation of these proteins remains to be determined. Furthermore, the details of the glycosylation biosynthetic process have not been determined in any of these systems. The definition of the precise role of glycosylation and the mechanism of biosynthesis will be facilitated by a detailed understanding of the genes involved. (C) 2002 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

Variabilidade genética em famílias de meios-irmãos de cafeeiro robusta

O cultivo do café é uma das atividades do agronegócio de maior importância socioeconômica dentre as diferentes atividades ligadas ao comércio agrícola mundial. Uma das maiores contribuições da genética quantitativa para o melhoramento genético é a possibilidade de prever ganhos genéticos. Quando diferentes critérios de seleção são considerados, a predição de ganhos referentes a cada critério tem grande importância, pois indica os melhoristas sobre como utilizar o material genético disponível, visando obter o máximo de ganhos possível para as características de interesse. O presente trabalho foi instalado em julho de 2004, na Fazenda Experimental de Bananal do Norte, conduzida pelo Incaper, no distrito de Pacotuba, município de Cachoeiro de Itapemirim, região Sul do Estado, com o objetivo de selecionar as melhores plantas entre e dentro de progênies de meios- irmãos de Coffea canephora, por meio de diferentes critérios de seleção. Foram realizadas análises de variância individuais e conjuntas para 26 progênies de meios- irmãos Coffea canephora. O delineamento experimental utilizado foi em blocos ao acaso com quatro testemunhas adicionais com quatro repetições e parcela composta por cinco plantas, com o espaçamento de 3,0 m x 1,2 m. Neste trabalho, considerou-se os dados das últimas cinco colheitas. As características mensuradas foram: florescimento, maturação, tamanho do grão, peso, porte, vigor, ferrugem, mancha cercóspora, seca de ponteiros, escala geral, porcentagem de frutos boia e bicho mineiro. Todas as análises estatísticas foram realizadas com o aplicativo computacional em genética e estatística (GENES). Foram estimados os ganhos de seleção em função da porcentagem de seleção de 20% entre e dentro, sendo as mesmas mantidas para todas as características. Todas as características foram submetidas a seleção no sentido positivo, exceto para florescimento, porte, ferrugem, mancha cercóspora, seca de ponteiros, porcentagem de frutos boia e bicho mineiro, para obter decréscimo em suas médias originais. Os critérios de seleção estudados foram: seleção convencional entre e dentro das famílias, índice de seleção combinada, seleção massal e seleção massal estratificada. Esta dissertação é composta por dois capítulos, em que foram realizadas análises biométricas, como a obtenção de estimativas de parâmetros genéticos. Na maioria das características estudadas, verificaram-se diferenças significativas (P<0,05) para genótipos que, associados aos coeficientes de variação genotípicos e também ao coeficiente de determinação genotípico e à relação CVg/CVe, indicam a existência de variabilidade genética nos materiais genéticos para a maioria das características e condições favoráveis para obtenção de ganhos genéticos pela seleção. Essas características também foram correlacionadas. Os dados foram submetidos às análises de variância e multivariada, aplicando-se a técnica de agrupamento e UPGMA, teste de médias e estudo de correlações. Na técnica de agrupamento, foi utilizada a distância generalizada de Mahalanobis como medida de dissimilaridade, e na delimitação dos grupos, o método de Tocher. Foi encontrada diversidade genética para as características associadas à qualidade fisiológica, mobilização de reserva das sementes, dimensões e biomassa das plântulas. Quatro grupos de genótipos puderam ser formados. Peso de massa seca de sementes, redução de reserva de sementes e peso de massa seca de plântulas estão positivamente correlacionados entre si, enquanto a redução de reserva das sementes e a eficiência na conversão dessas reservas em plântulas estão negativamente correlacionadas. De acordo com os resultados obtidos, verificou-se que todas as características apresentaram níveis diferenciados de variabilidade genética e os critérios de seleção utilizados mostraram-se eficientes para o melhoramento, no qual o índice de seleção combinada é o critério de seleção que apresentou os melhores resultados em termos de ganhos, sendo indicado como critério mais apropriado para o melhoramento genético da população estudada. Nos estudos de correlações, em 70% dos casos, a correlação fenotípica foi superior à genotípica, mostrando maior influência dos fatores ambientais em relação aos genotípicos e condições propícias ao melhoramento dos diferentes caracteres. No estudo de divergência genética, observou-se que pelo agrupamento de genótipos, pela técnica de Tocher, indicou que os genótipos foram distribuídos em três grupos.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

Statistical motion learning for improved transform domain Wyner-Ziv video coding

Wyner - Ziv (WZ) video coding is a particular case of distributed video coding (DVC), the recent video coding paradigm based on the Slepian - Wolf and Wyner - Ziv theorems which exploits the source temporal correlation at the decoder and not at the encoder as in predictive video coding. Although some progress has been made in the last years, WZ video coding is still far from the compression performance of predictive video coding, especially for high and complex motion contents. The WZ video codec adopted in this study is based on a transform domain WZ video coding architecture with feedback channel-driven rate control, whose modules have been improved with some recent coding tools. This study proposes a novel motion learning approach to successively improve the rate-distortion (RD) performance of the WZ video codec as the decoding proceeds, making use of the already decoded transform bands to improve the decoding process for the remaining transform bands. The results obtained reveal gains up to 2.3 dB in the RD curves against the performance for the same codec without the proposed motion learning approach for high motion sequences and long group of pictures (GOP) sizes.

Risk factors for metabolic bone disease in Crohn's disease patients

Background: The aim was to evaluate the presence of metabolic bone disease (MBD) in patients with Crohn’s disease (CD) and to identify potential etiologic factors. Methods: The case–control study included 99 patients with CD and 56 controls with a similar age and gender distribution. Both groups had dual-energy x-ray absorptionmetry and a nutritional evaluation. Single nucleotide polymorphisms at the IL1, TNF-a, LTa, and IL-6 genes were analyzed in patients only. Statistical analysis was performed using SPSS software. Results: The prevalence of MBD was significantly higher in patients (P ¼ 0.006). CD patients with osteoporosis were older (P < 0.005), small bowel involvement and surgical resections were more frequent (P < 0.005), they more often exhibited a penetrating or stricturing phenotype (P < 0.05), duration of disease over 15 years (P < 0.005), and body mass index (BMI) under 18.5 kg/m2 (P < 0.01) were more often found. No association was found with steroid use. Patients with a Z-score < 2.0 more frequently had chronic active disease (P < 0.05). With regard to diet, low vitamin K intake was more frequent (P ¼ 0.03) and intake of total, monounsaturated, and polyunsaturated fat was higher in patients with Z-score < 2.0 (P < 0.05). With respect to genetics, carriage of the polymorphic allele for LTa252 A/G was associated with a higher risk of osteoporosis (P ¼ 0.02). Regression analysis showed that age over 40 years, chronic active disease, and previous colonic resections were independently associated with the risk of developing MBD. Conclusions: The prevalence of MBD was significantly higher in CD patients. Besides the usual risk factors, we observed that factors related to chronic active and long-lasting disease increased the risk of MBD.

Analysis of tongue shape and motion in speech production using statistical modeling

The mechanisms of speech production are complex and have been raising attention from researchers of both medical and computer vision fields. In the speech production mechanism, the articulator’s study is a complex issue, since they have a high level of freedom along this process, namely the tongue, which instigates a problem in its control and observation. In this work it is automatically characterized the tongues shape during the articulation of the oral vowels of Portuguese European by using statistical modeling on MR-images. A point distribution model is built from a set of images collected during artificially sustained articulations of Portuguese European sounds, which can extract the main characteristics of the motion of the tongue. The model built in this work allows under standing more clearly the dynamic speech events involved during sustained articulations. The tongue shape model built can also be useful for speech rehabilitation purposes, specifically to recognize the compensatory movements of the articulators during speech production.

Statistical analysis of quality control measurements in IMRT for head and neck and prostate cancer

Intensity Modulated Radiotherapy (IMRT) is a technique introduced to shape more precisely the dose distributions to the tumour, providing a higher dose escalation in the volume to irradiate and simultaneously decreasing the dose in the organs at risk which consequently reduces the treatment toxicity. This technique is widely used in prostate and head and neck (H&N) tumours. Given the complexity and the use of high doses in this technique it’s necessary to ensure as a safe and secure administration of the treatment, through the use of quality control programmes for IMRT. The purpose of this study was to evaluate statistically the quality control measurements that are made for the IMRT plans in prostate and H&N patients, before the beginning of the treatment, analysing their variations, the percentage of rejected and repeated measurements, the average, standard deviations and the proportion relations.

A few what-ifs on using statistical analysis of stochastic simulation runs to extract timeliness properties

Modern real-time systems, with a more flexible and adaptive nature, demand approaches for timeliness evaluation based on probabilistic measures of meeting deadlines. In this context, simulation can emerge as an adequate solution to understand and analyze the timing behaviour of actual systems. However, care must be taken with the obtained outputs under the penalty of obtaining results with lack of credibility. Particularly important is to consider that we are more interested in values from the tail of a probability distribution (near worst-case probabilities), instead of deriving confidence on mean values. We approach this subject by considering the random nature of simulation output data. We will start by discussing well known approaches for estimating distributions out of simulation output, and the confidence which can be applied to its mean values. This is the basis for a discussion on the applicability of such approaches to derive confidence on the tail of distributions, where the worst-case is expected to be.

From simulation to statistical analysis: timeliness assessment of ethernet/IP-based distributed systems

A number of characteristics are boosting the eagerness of extending Ethernet to also cover factory-floor distributed real-time applications. Full-duplex links, non-blocking and priority-based switching, bandwidth availability, just to mention a few, are characteristics upon which that eagerness is building up. But, will Ethernet technologies really manage to replace traditional Fieldbus networks? Ethernet technology, by itself, does not include features above the lower layers of the OSI communication model. In the past few years, it is particularly significant the considerable amount of work that has been devoted to the timing analysis of Ethernet-based technologies. It happens, however, that the majority of those works are restricted to the analysis of sub-sets of the overall computing and communication system, thus without addressing timeliness at a holistic level. To this end, we are addressing a few inter-linked research topics with the purpose of setting a framework for the development of tools suitable to extract temporal properties of Commercial-Off-The-Shelf (COTS) Ethernet-based factory-floor distributed systems. This framework is being applied to a specific COTS technology, Ethernet/IP. In this paper, we reason about the modelling and simulation of Ethernet/IP-based systems, and on the use of statistical analysis techniques to provide usable results. Discrete event simulation models of a distributed system can be a powerful tool for the timeliness evaluation of the overall system, but particular care must be taken with the results provided by traditional statistical analysis techniques.