Supercoiling, knotting and replication fork reversal in partially replicated plasmids.

To study the structure of partially replicated plasmids, we cloned the Escherichia coli polar replication terminator TerE in its active orientation at different locations in the ColE1 vector pBR18. The resulting plasmids, pBR18-TerE@StyI and pBR18-TerE@EcoRI, were analyzed by neutral/neutral two-dimensional agarose gel electrophoresis and electron microscopy. Replication forks stop at the Ter-TUS complex, leading to the accumulation of specific replication intermediates with a mass 1.26 times the mass of non-replicating plasmids for pBR18-TerE@StyI and 1.57 times for pBR18-TerE@EcoRI. The number of knotted bubbles detected after digestion with ScaI and the number and electrophoretic mobility of undigested partially replicated topoisomers reflect the changes in plasmid topology that occur in DNA molecules replicated to different extents. Exposure to increasing concentrations of chloroquine or ethidium bromide revealed that partially replicated topoisomers (CCCRIs) do not sustain positive supercoiling as efficiently as their non-replicating counterparts. It was suggested that this occurs because in partially replicated plasmids a positive DeltaLk is absorbed by regression of the replication fork. Indeed, we showed by electron microscopy that, at least in the presence of chloroquine, some of the CCCRIs of pBR18-Ter@StyI formed Holliday-like junction structures characteristic of reversed forks. However, not all the positive supercoiling was absorbed by fork reversal in the presence of high concentrations of ethidium bromide.

Fusion of data sets in multivariate linear regression with errors-in-variables

We consider the application of normal theory methods to the estimation and testing of a general type of multivariate regressionmodels with errors--in--variables, in the case where various data setsare merged into a single analysis and the observable variables deviatepossibly from normality. The various samples to be merged can differ on the set of observable variables available. We show that there is a convenient way to parameterize the model so that, despite the possiblenon--normality of the data, normal--theory methods yield correct inferencesfor the parameters of interest and for the goodness--of--fit test. Thetheory described encompasses both the functional and structural modelcases, and can be implemented using standard software for structuralequations models, such as LISREL, EQS, LISCOMP, among others. An illustration with Monte Carlo data is presented.

Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI.

BACKGROUND AND PURPOSE: MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI. MATERIALS AND METHODS: Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs. RESULTS: The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI. CONCLUSIONS: Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Retinal degeneration progression changes lentiviral vector cell targeting in the retina.

In normal mice, the lentiviral vector (LV) is very efficient to target the RPE cells, but transduces retinal neurons well only during development. In the present study, the tropism of LV has been investigated in the degenerating retina of mice, knowing that the retina structure changes during degeneration. We postulated that the viral transduction would be increased by the alteration of the outer limiting membrane (OLM). Two different LV pseudotypes were tested using the VSVG and the Mokola envelopes, as well as two animal models of retinal degeneration: light-damaged Balb-C and Rhodopsin knockout (Rho-/-) mice. After light damage, the OLM is altered and no significant increase of the number of transduced photoreceptors can be obtained with a LV-VSVG-Rhop-GFP vector. In the Rho-/- mice, an alteration of the OLM was also observed, but the possibility of transducing photoreceptors was decreased, probably by ongoing gliosis. The use of a ubiquitous promoter allows better photoreceptor transduction, suggesting that photoreceptor-specific promoter activity changes during late stages of photoreceptor degeneration. However, the number of targeted photoreceptors remains low. In contrast, LV pseudotyped with the Mokola envelope allows a wide dispersion of the vector into the retina (corresponding to the injection bleb) with preferential targeting of Müller cells, a situation which does not occur in the wild-type retina. Mokola-pseudotyped lentiviral vectors may serve to engineer these glial cells to deliver secreted therapeutic factors to a diseased area of the retina.

Promoção do Auto-cuidado em utentes com Hipertensão Arterial

O presente estudo faz uma abordagem geral em termos bibliográficos sobre a hipertensão arterial dado a sua importância epidemiológica a nível mundial, centrada na óptica da enfermagem, utilizando o modelo teórico de Dorohteia Orem – Teoria de Deficit de Auto-cuidado, mostrando a sua aplicação prática juntos dos utentes hipertensos de Lagoa – Rª das Patas. Tratando-se de uma comunidade com carências várias, procuramos estabelecer relações entre esses factores e a hipertensão. Fizemos um levantamento geral em termos demográficos da pequena povoação; ficamos a saber da distribuição populacional por faixa etária, identificando a população alvo do nosso trabalho (hipertensos dos 45 a 85 anos); conhecer o comportamento dos utentes perante os factores de riscos; identificar os deficits de auto-cuidado, promover o auto-cuidado através de visitas domiciliárias, interagindo com o hipertenso no seu meio familiar, no intuito de satisfazer a sua necessidade no que concerne ao tratamento e controle do nível da pressão arterial, proporcionando-lhe um atendimento personalizado, contribuindo assim, para melhoria da sua qualidade de vida.

Morphometric shape analysis using learning vector quantization neural networks - an example distinguishing two microtine vole species

Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.

Consumer Advisory Bulletin, Take the Scare Out of Auto Repair!, February 2007

The Attorney General’s Consumer Protection Division receives hundreds of calls and consumer complaints every year. Follow these tips to avoid unexpected expense and disappointments. This record is about: Take the Scare Out of Auto Repair!

Consumer Advisory Bulletin, Take the Scare Out of Auto Repair!, February 2007

The Attorney General’s Consumer Protection Division receives hundreds of calls and consumer complaints every year. Follow these tips to avoid unexpected expense and disappointments. This record is about: Take the Scare Out of Auto Repair!