Trypanosoma cruzi: expression of antigenic component 5 among 35 laboratory clones obtained from 18 different isozymic variants

Two monoclonal antibodies anti-component 5 of Trypanosoma cruzi (I-35/115 and II-190/30) were tested in IFA and ELISA respectively against 35 T. cruzi laboratory clones. Among the 35 clones tested, 18 different isozyme patterns were detected. All clones were recognized by both monoclonal antibodies except one clone which did not react with II-190/30. These results support the universal expression of specific component 5 within the taxon T. cruzi.

Multiple linear and principal component regressions for modelling ecotoxicity bioassay response

The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response.With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Leça river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Leça River.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Principal component analysis of the yield curve

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Healing replicas in a software component replication system

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

An assessment of the integration of the mental health component into the care of women affected by intimate partner violence in Peru

RESUMO: A violência contra as mulheres (VCM) é um problema de saúde pública e uma violação dos direitos humanos. Ele tem uma alta prevalência na América Latina e no Caribe; o Estudo da Violência Contra as Mulheres da Organização Mundial de Saúde (OMS) identificou que as mulheres peruanas sofrem o maior índice de violência. O Perú é signatário da CEDAW e da Convenção de Belém do Pará, com recomendações para resolver este tipo de discriminação e descrever o papel do setor da saúde. A lei peruana define a violência como um problema de saúde mental. Objectivos: As três orientações clínicas do Ministério da Saúde para avaliar a integração da componente de saúde mental no cuidado de mulheres afetadas pela VCM foram revistas. Método: A proteção da saúde mental foi avaliada nas orientações acima mencionadas. A lei peruana relevante para perceber o reconhecimento das consequências de VCM na saúde mental e os cuidados prestados neste contexto foram revistos. Usando esses padrões nacionais e internacionais, foi realizada uma análise de conteúdo dos guias peruanos para a atenção da violência para ver como eles se integram a saúde mental. Resultados: Estas orientações são muito extensas e não definem claramente a responsabilidade dos profissionais de saúde. Não incluem um exame de saúde mental na avaliação da vítima e são vagas na descrição das atividades a serem realizadas pelo prestador dos cuidados de saúde. As orientações recomendam uma triagem universal usando um instrumento com formato antiquado e pesado. Em contrapartida, as orientações da OMS não recomendam qualquer triagem. Conclusão: As várias orientações analisadas não fornecem a informação necessária para o profissional de saúde avaliar o envolvimento da saúde mental e, desnecessariamente, tratam as mulheres sobreviventes de VCM como doentes mentais. Recomenda-se que as orientações recentes da OMS (Responding to intimate partner violence and sexual violence against women: WHO clinical and policy guidelines, 2013) para os cuidados de VCM sejam usadas como um modelo para o desenvolvimento de um único dispositivo técnico que incorpora directrizes com base científica. legislação com base no género, saúde, guias, prevenção e mujeres 6 RESUMO (PORTUGUESE) A violência contra as mulheres (VCM) é um problema de saúde pública e uma violação dos direitos humanos. Ele tem uma alta prevalência na América Latina e no Caribe; o Estudo da Violência Contra as Mulheres da Organização Mundial de Saúde (OMS) identificou que as mulheres peruanas sofrem o maior índice de violência. O Perú é signatário da CEDAW e da Convenção de Belém do Pará, com recomendações para resolver este tipo de discriminação e descrever o papel do setor da saúde. A lei peruana define a violência como um problema de saúde mental. Objectivos: As três orientações clínicas do Ministério da Saúde para avaliar a integração da componente de saúde mental no cuidado de mulheres afetadas pela VCM foram revistas. Método: A proteção da saúde mental foi avaliada nas orientações acima mencionadas. A lei peruana relevante para perceber o reconhecimento das consequências de VCM na saúde mental e os cuidados prestados neste contexto foram revistos. Usando esses padrões nacionais e internacionais, foi realizada uma análise de conteúdo dos guias peruanos para a atenção da violência para ver como eles se integram a saúde mental. Resultados: Estas orientações são muito extensas e não definem claramente a responsabilidade dos profissionais de saúde. Não incluem um exame de saúde mental na avaliação da vítima e são vagas na descrição das atividades a serem realizadas pelo prestador dos cuidados de saúde. As orientações recomendam uma triagem universal usando um instrumento com formato antiquado e pesado. Em contrapartida, as orientações da OMS não recomendam qualquer triagem. Conclusão: As várias orientações analisadas não fornecem a informação necessária para o profissional de saúde avaliar o envolvimento da saúde mental e, desnecessariamente, tratam as mulheres sobreviventes de VCM como doentes mentais. Recomenda-se que as orientações recentes da OMS (Responding to intimate partner violence and sexual violence against women: WHO clinical and policy guidelines, 2013) para os cuidados de VCM sejam usadas como um modelo para o desenvolvimento de um único dispositivo técnico que incorpora directrizes com base científica.-----------------ABSTRACT: Violence against women (VAW) is a public health problem and a human rights violation. It is highly prevalent in Latin America and the Caribbean; the Multi-country Study on Violence against Women by the World Health Organization identified rural Peruvian women as suffering the highest rates of VAW. The country is party to CEDAW and Belen Do Para Conventions, which set forth recommendations to overcome this form of discrimination and describe the role of the health sector. Peruvian law defines violence as a mental health issue. Objective: The Ministry of Health’s three technical guidelines were reviewed to assess the integration of mental health into the care of women affected by violence Method: The protection of the woman’s mental health was ascertained in the conventions mentioned above. The recognition of the mental health consequences of VAW and the inclusion of its evaluation and care were assessed in pertinent Peruvian legislation. Using these international and national parameters, the three guidelines for the attention of violence were subject to content analysis to see whether they conform to the conventions and integrate mental health care. Outcome: These guidelines are too extensive and do not clearly define the responsibility of health workers. They do not include a mental health exam in the evaluation of the victim and are vague in the description of the actions to be carried out by the health care provider. Guidelines prescribe universal screening using an outdated instrument and moreover, WHO Guidelines do not recommend screening. Conclusion: These multiple guidelines do not provide useful guidance for health care providers, particularly for the assessment of mental health sequelae, and unnecessarily stigmatize survivors of violence as mentally ill. It is recommended that the World Health Organization’s document Responding to intimate partner violence and sexual violence against women: WHO clinical and policy guidelines (2013) be used as a blueprint for only one technical instrument that incorporates evidence -based national policy and guidelines.

Electrohysterogram signal component cataloging with spectral and time-frequency methods

The Electrohysterogram (EHG) is a new instrument for pregnancy monitoring. It measures the uterine muscle electrical signal, which is closely related with uterine contractions. The EHG is described as a viable alternative and a more precise instrument than the currently most widely used method for the description of uterine contractions: the external tocogram. The EHG has also been indicated as a promising tool in the assessment of preterm delivery risk. This work intends to contribute towards the EHG characterization through the inventory of its components which are: • Contractions; • Labor contractions; • Alvarez waves; • Fetal movements; • Long Duration Low Frequency Waves; The instruments used for cataloging were: Spectral Analysis, parametric and non-parametric, energy estimators, time-frequency methods and the tocogram annotated by expert physicians. The EHG and respective tocograms were obtained from the Icelandic 16-electrode Electrohysterogram Database. 288 components were classified. There is not a component database of this type available for consultation. The spectral analysis module and power estimation was added to Uterine Explorer, an EHG analysis software developed in FCT-UNL. The importance of this component database is related to the need to improve the understanding of the EHG which is a relatively complex signal, as well as contributing towards the detection of preterm birth. Preterm birth accounts for 10% of all births and is one of the most relevant obstetric conditions. Despite the technological and scientific advances in perinatal medicine, in developed countries, prematurity is the major cause of neonatal death. Although various risk factors such as previous preterm births, infection, uterine malformations, multiple gestation and short uterine cervix in second trimester, have been associated with this condition, its etiology remains unknown [1][2][3].

A VEP study in sleeping and awake one-month-old infants and its relation with social behavior

With the present study we aimed to analyze the relationship between infants' behavior and their visual evoked-potential (VEPs) response. Specifically, we want to verify differences regarding the VEP response in sleeping and awake infants and if an association between VEP components, in both groups, with neurobehavioral outcome could be identified. To do so, thirty-two full-term and healthy infants, approximately 1-month of age, were assessed through a VEP unpatterned flashlight stimuli paradigm, offered in two different intensities, and were assessed using a neurobehavioral scale. However, only 18 infants have both assessments, and therefore, these is the total included in both analysis. Infants displayed a mature neurobehavioral outcome, expected for their age. We observed that P2 and N3 components were present in both sleeping and awake infants. Differences between intensities were found regarding the P2 amplitude, but only in awake infants. Regression analysis showed that N3 amplitude predicted an adequate social interactive and internal regulatory behavior in infants who were awake during the stimuli presentation. Taking into account that social orientation and regulatory behaviors are fundamental keys for social-like behavior in 1-month-old infants, this study provides an important approach for assessing physiological biomarkers (VEPs) and its relation with social behavior, very early in postnatal development. Moreover, we evidence the importance of the infant's state when studying differences regarding visual threshold processing and its association with behavioral outcome.

Mechanisms of reproductive isolation between an ant species of hybrid origin and one of its parents.

The establishment of new species by hybridization is difficult because it requires the development of reproductive isolation (RI) in sympatry to escape the homogenizing effects of gene flow from the parental species. Here we investigated the role of two pre- and two postzygotic mechanisms of RI in a system comprising two interdependent Pogonomyrmex harvester ant lineages (the H1 and H2 lineages) of hybrid origin and one of their parental species (P. rugosus). Similar to most other ants, P. rugosus is characterized by an environmental system of caste determination with female brood developing either into queens or workers depending on nongenetic factors. By contrast, there is a strong genetic component to caste determination in the H1 and H2 lineages because the developmental fate of female brood depends on the genetic origin of the parents, with interlineage eggs developing into workers and intralineage eggs developing into queens. The study of a mixed mating aggregation revealed strong differences in mating flight timing between P. rugosus and the two lineages as a first mechanism of RI. A second important prezygotic mechanism was assortative mating. Laboratory experiments also provided support for one of the two investigated mechanisms of postzygotic isolation. The majority of offspring produced from the few matings between P. rugosus and the lineages aborted at the egg stage. This hybrid inviability was under maternal influence, with hybrids produced by P. rugosus queens being always inviable whereas a small proportion of H2 lineage queens produced large numbers of adult hybrid offspring. Finally, we found no evidence that genetic caste determination acted as a second postzygotic mechanism reducing gene flow between P. rugosus and the H lineages. The few viable P. rugosus-H hybrids were not preferentially shunted into functionally sterile workers but developed into both workers and queens. Overall, these results reveal that the nearly complete (99.5%) RI between P. rugosus and the two hybrid lineages stems from the combination of two typical prezygotic mechanisms (mating time divergence and assortative mating) and one postzygotic mechanism (hybrid inviability).

Engineering, conjugation, and immunogenicity assessment of Escherichia coli O121 O antigen for its potential use as a typhoid vaccine component.

State-of-the-art production technologies for conjugate vaccines are complex, multi-step processes. An alternative approach to produce glycoconjugates is based on the bacterial N-linked protein glycosylation system first described in Campylobacter jejuni. The C. jejuni N-glycosylation system has been successfully transferred into Escherichia coli, enabling in vivo production of customized recombinant glycoproteins. However, some antigenic bacterial cell surface polysaccharides, like the Vi antigen of Salmonella enterica serovar Typhi, have not been reported to be accessible to the bacterial oligosaccharyltransferase PglB, hence hamper development of novel conjugate vaccines against typhoid fever. In this report, Vi-like polysaccharide structures that can be transferred by PglB were evaluated as typhoid vaccine components. A polysaccharide fulfilling these requirements was found in Escherichia coli serovar O121. Inactivation of the E. coli O121 O antigen cluster encoded gene wbqG resulted in expression of O polysaccharides reactive with antibodies raised against the Vi antigen. The structure of the recombinantly expressed mutant O polysaccharide was elucidated using a novel HPLC and mass spectrometry based method for purified undecaprenyl pyrophosphate (Und-PP) linked glycans, and the presence of epitopes also found in the Vi antigen was confirmed. The mutant O antigen structure was transferred to acceptor proteins using the bacterial N-glycosylation system, and immunogenicity of the resulting conjugates was evaluated in mice. The conjugate-induced antibodies reacted in an enzyme-linked immunosorbent assay with E. coli O121 LPS. One animal developed a significant rise in serum immunoglobulin anti-Vi titer upon immunization.

Does the mechanical work in running change during the VO2 slow component?

PURPOSE: The origin of the slow component is not fully understood. The mechanical hypothesis is one of the potential factors, because an increase in external mechanical work with fatigue was previously reported for a constant velocity run. The purpose of this study was to determine whether a change in mechanical work could occur during the development of the VO2 slow component under the effect of fatigue. METHODS: Twelve regional-level competitive runners performed a square-wave transition, corresponding to 95% of the speed associated with peak VO2 obtained during an incremental test. The VO2 response was fit with a classical model including two exponential functions. A specific treadmill with three-dimensional force transducers was used to measure the ground reaction force. Kinetic work (W(kin)), potential work (W(pot)), external work (W(ext)), and an index of internal work (W(int)) per unit of distance were quantified continuously. RESULTS: During the slow component of VO2, a significant increase in W (P< 0.01), no change in W, and a significant decrease in W and W index (P< 0.05, P< 0.001, respectively) were observed. CONCLUSION: The present study showed that the slow component of VO2 did not result partly from a change in mechanical work under the effect of fatigue. Nevertheless, the decrease in stride frequency (P< 0.001) and contact time (P< 0.001) suggested an alternative mechanical explanation. The slow component during running may be due to the cost of generating force or to alterations in the storage and recoil of elastic energy, and not to the external mechanical work.

Tibial component positioning in total knee arthroplasty: bone coverage and extensor apparatus alignment.

Correct positioning of the tibial component in total knee arthroplasty (TKA) must take into account both an optimal bone coverage (defined by a maximal cortical bearing with posteromedial and anterolateral support) and satisfactory patellofemoral tracking. Consequently, a compromise position must be found by the surgeon during the operation to simultaneously meet these two requirements. Moreover, tibial tray positioning depends upon the tibial torsion, which has been shown to act mainly in the proximal quarter of the tibia. Therefore, the correct application of the tibial tray is also theoretically related to the level of bone resection. In this study, we first quantified the torsional profile given by an optimal bone coverage for a symmetrical tibial tray design and for an asymmetrical one. Then, for the two types of tibial trays, we measured the angle difference between optimal bone coverage and an alignment on the middle of the tibial tubercule. Results showed that the values of the torsional profile given by the symmetrical tray were more scattered than those from the asymmetrical one. However, determination of the mean differential angle between the position providing optimal bone coverage and the one providing the best patellofemoral tracking indicated that the symmetrical prosthetic tray offered the best compromise between these two requirements. Although the tibiofemoral joint is known to be asymmetric in both shape and dimension, the asymmetrical tray chosen in this study was found to fulfill this compromise with more difficulty.

A chemical Hamiltonian approach study of the basis set superposition error changes on electron densities and one- and two-center energy components

A comparision of the local effects of the basis set superposition error (BSSE) on the electron densities and energy components of three representative H-bonded complexes was carried out. The electron densities were obtained with Hartee-Fock and density functional theory versions of the chemical Hamiltonian approach (CHA) methodology. It was shown that the effects of the BSSE were common for all complexes studied. The electron density difference maps and the chemical energy component analysis (CECA) analysis confirmed that the local effects of the BSSE were different when diffuse functions were present in the calculations

Capacity to within one bit of a class of Gaussian multicast channels with interference

This paper studies the fundamental operational limits of a class of Gaussian multicast channels with an interference setting. In particular, the paper considers two base stations multicasting separate messages to distinct sets of users. In the presence of channel state information at the transmitters and at the respective receivers, the capacity region of the Gaussian multicast channel with interference is characterized to within one bit. At the crux of this result is an extension to the multicast channel with interference of the Han-Kobayashi or the Chong-Motani-Garg achievable region for the interference channel.