An Attempt to Analyse Baarda’s Iterative Data Snooping Procedure based on Monte Carlo Simulation

William Sealy Gosset, otherwise known as “Student”, Fisher's disciple, was one of the pioneers in the development of modern statistical method and its application to the design and analysis of experiments. Although there were no computers in his time, he discovered the form of the “t distribution” by a combination of mathematical and empirical work with random numbers. This is now known as an early application of the Monte Carlo simulation. Today with the fast computers and large data storage systems, the probabilities distribution can be estimated using computerized simulation. Here, we use Monte Carlo simulation to investigate the efficiency of the Baarda’s iterative data snooping procedure as test statistic for outlier identification in the Gauss-Markov model. We highlight that the iterative data snooping procedure can identify more observations than real number of outliers simulated. It has a deserved attention in this work. The available probability of over-identification allows enhancing the probability of type III error as well as probably the outlier identifiability. With this approach, considering the analysed network, in general, the significance level of 0.001 was the best scenario to not make mistake of excluding wrong observation. Thus, the data snooping procedure was more realistic when the over-identifications case is considered in the simulation. In the end, we concluded that for GNSS network that the iterative data snooping procedure based on Monte Carlo can locate an outlier in the order of magnitude 4.5σ with high success rate

New Recombinant Mycobacterium bovis BCG Expression Vectors: Improving Genetic Control over Mycobacterial Promoters.

The expression of many antigens, stimulatory molecules, or even metabolic pathways in mycobacteria such as Mycobacterium bovis BCG or M. smegmatis was made possible through the development of shuttle vectors, and several recombinant vaccines have been constructed. However, gene expression in any of these systems relied mostly on the selection of natural promoters expected to provide the required level of expression by trial and error. To establish a systematic selection of promoters with a range of strengths, we generated a library of mutagenized promoters through error-prone PCR of the strong PL5 promoter, originally from mycobacteriophage L5. These promoters were cloned upstream of the enhanced green fluorescent protein reporter gene, and recombinant M. smegmatis bacteria exhibiting a wide range of fluorescence levels were identified. A set of promoters was selected and identified as having high (pJK-F8), intermediate (pJK-B7, pJK-E6, pJK-D6), or low (pJK-C1) promoter strengths in both M. smegmatis and M. bovisBCG. The sequencing of the promoter region demonstrated that it was extensively modified (6 to 11%) in all of the plasmids selected. To test the functionality of the system, two different expression vectors were demonstrated to allow corresponding expression levels of the Schistosoma mansoni antigen Sm29 in BCG. The approach used here can be used to adjust expression levels for synthetic and/or systems biology studies or for vaccine development to maximize the immune response

Global Optimization of Redescending Robust Estimators

[EN] Robust estimation has proved to be a valuable alternative to the least squares estimator for the cases where the dataset is contaminated with outliers. Many robust estimators have been designed to be minimally affected by the outlying observations and produce a good fit for the majority of the data. Among them, the redescending estimators have demonstrated the best estimation capabilities. It is little known, however, that the success of a robust estimation method depends not only on the robust estimator used but also on the way the estimator is computed. In the present paper, we show that for complicated cases, the predominant method of computing the robust estimator by means of an iteratively reweighted least squares scheme may result in a local optimum of significantly lower quality than the global optimum attainable by means of a global optimization method. Further, the sequential use of the proposed global robust estimation proves to successfully solve the problem of M-split estimation, that is, the determination of parameters of different functional models implicit in the data.Baselga Moreno, S.; Klein, I.; Sampaio Suraci, S.; Castro De Oliveira, L.; Tomio Matsuoka, M.; Francisco Rofatto, V. (2021). Global Optimization of Redescending Robust Estimators. Mathematical Problems in Engineering. 2021:1-13. https://doi.org/10.1155/2021/9929892S113202

An attempt to analyse Iterative Data Snooping and L1-norm based on Monte Carlo simulation in the context of leveling networks

[EN] The goal of this paper is to evaluate the outlier identification performance of iterative Data Snooping (IDS) and L-1-norm in levelling networks by considering the redundancy of the network, number and size of the outliers. For this purpose, several Monte-Carlo experiments were conducted into three different levelling networks configurations. In addition, a new way to compare the results of IDS based on Least Squares (LS) residuals and robust estimators such as the L-1-norm has also been developed and presented. From the perspective of analysis only according to the success rate, it is shown that L-1-norm performs better than IDS for the case of networks with low redundancy ((r) over bar < 0.5), especially for cases where more than one outlier is present in the dataset. In the relationship between false positive rate and outlier identification success rate, however, IDS performs better than L-1-norm, independently of the levelling network configuration, number and size of outliers.Klein, I.; Suraci, SS.; De Oliveira, LC.; Rofatto, VF.; Matsuoka, MT.; Baselga Moreno, S. (2022). An attempt to analyse Iterative Data Snooping and L1-norm based on Monte Carlo simulation in the context of leveling networks. Survey Review. 54(382):70-78. https://doi.org/10.1080/00396265.2021.187833870785438

Performance comparison of least squares, iterative and global L1 Norm minimization and exhaustive search methods for outlier detection in leveling networks

[EN] Different approaches have been proposed to determine the possible outliers existing in a dataset. The most widely used consists in the application of the data snooping test over the least squares adjustment results. This strategy is very likely to succeed for the case of zero or one outliers but, contrary to what is often assumed, the same is not valid for the multiple outlier case, even in its iterative application scheme. Robust estimation, computed by iteratively reweighted least squares or a global optimization method, is other alternative approach which often produces good results in the presence of outliers, as is the case of exhaustive search methods that explore elimination of every possible set of observations. General statements, having universal validity, about the best way to compute a geodetic network with multiple outliers are impossible to be given due to the many different factors involved (type of network, number and size of possible errors, available computational force, etc.). However, we see in this paper that some conclusions can be drawn for the case of a leveling network, which has a certain geometrical simplicity compared with planimetric or three-dimensional networks though a usually high number of unknowns and relatively low redundancy. Among other results, we experience the occasional failure in the iterative application of the data snooping test, the relatively successful results obtained by both methods computing the robust estimator, which perform equivalently in this case, and the successful application of the exhaustive search method, for different cases that become increasingly intractable as the number of outliers approaches half the number of degrees of freedom of the network.Baselga Moreno, S.; Klein, I.; Suraci, SS.; Castro De Oliveira, L.; Matsuoka, MT.; Rofatto, VF. (2020). Performance comparison of least squares, iterative and global L1 Norm minimization and exhaustive search methods for outlier detection in leveling networks. Acta Geodynamica et Geomaterialia. 17(4):425-438. https://doi.org/10.13168/AGG.2020.003142543817

INTRODUÇÃO E APLICAÇÃO DA DILUIÇÃO DA PRECISÃO DAS AMBIGUIDADES GNSS – ADOP

Diluição da precisão das ambiguidades GNSS, conhecida como ADOP (AmbiguityDilution of Precision), é o tópico principal deste artigo. Basicamente, o ADOP édefinido como uma medida escalar para avaliar a precisão das ambiguidades reais(float). Assim, entre as inúmeras possibilidades, a ADOP pode auxiliar na previsãodo comportamento de uma linha base ou de uma rede de receptores GNSS no quediz respeito ao problema de solução das ambiguidades envolvidas, quer seja emtempo real (instantânea), ou no modo pós-processado. A vantagem de utilizar agrandeza ADOP advém da possibilidade de extrair uma expressão analíticasimplificada, considerando os diversos fatores que afetam a resolução dasambiguidades. Além disso, essa grandeza traz informação a respeito da taxa desucesso de resolução das ambiguidades. As expressões utilizadas nesse artigo levamem consideração alguns fatores, como por exemplo, informações a priori daprecisão das medidas de fase da onda portadora e pseudodistância, número deestações e satélites, número de frequências disponíveis e o comportamento daatmosfera, considerando tanto a troposfera como a ionosfera. A partir dessasinformações, diversos cenários são factíveis de serem estabelecidos visando analisaro impacto de cada informação particular na resolução das ambiguidades. As análisesforam realizadas no contexto de algumas estações da rede GNSS-SP, uma redeGNSS estabelecida no Estado de São Paulo

Schistosoma mansoni venom allergen-like proteins:Phylogenetic relationships, stage-specific transcription and tissue localization as predictors of immunological cross-reactivity

O artigo encontra-se disponível para download no site do Editor.Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2019-07-15T18:23:01Z No. of bitstreams: 1 Farias, L.P. Schistosoma mansoni venom...2019.pdf: 1118803 bytes, checksum: 1ddd953840abbbd5d56675c8d6c4fa6e (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2019-07-15T18:39:31Z (GMT) No. of bitstreams: 1 Farias, L.P. Schistosoma mansoni venom...2019.pdf: 1118803 bytes, checksum: 1ddd953840abbbd5d56675c8d6c4fa6e (MD5)Made available in DSpace on 2019-07-15T18:39:31Z (GMT). No. of bitstreams: 1 Farias, L.P. Schistosoma mansoni venom...2019.pdf: 1118803 bytes, checksum: 1ddd953840abbbd5d56675c8d6c4fa6e (MD5) Previous issue date: 2019Welcome Trust (UK) (WT084273/Z/07/Z) to KFH, Fundação Butantan, Fundação de Amparo à Pesquisa do Estado de São Paulo (Brazil) to LPF and LLC (2012/23124-4), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) to LCCL and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001, and by fellowships from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, Brazil) to LPF (2008/57946-5) and HKF (2007/07685-8) and from CNPq to MIK (160861/2017-9). We thank Dra. Eliana Nakano and Ms. Patricia A. Miyasato for supplying the parasite stages and to Alexsander Seixas de Souza for confocal microscopy (FAPESP 00/11624-5) imaging support, all from Instituto Butantan, Brazil.Instituto Butantan. Centro de Biotecnologia. São Paulo, SP, Brasil / Fundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil.Aberystwyth University. Institute of Biological. Environmental and Rural Sciences. Aberystwyth, UK.Aberystwyth University. Institute of Biological. Environmental and Rural Sciences. Aberystwyth, UK.Instituto Butantan. Centro de Biotecnologia. São Paulo, SP, Brasil.Aberystwyth University. Institute of Biological. Environmental and Rural Sciences. Aberystwyth, UK.Aberystwyth University. Institute of Biological. Environmental and Rural Sciences. Aberystwyth, UK.Fundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, Brasil.Instituto Butantan. Centro de Biotecnologia. São Paulo, SP, Brasil / Universidade de São Paulo. Pós-Graduação Interunidades em Biotecnologia. São Paulo, SP, Brasil.Leiden University Medical Centre. Center for Proteomics and Metabolomics. RC Leiden, The Netherlands.Leiden University Medical Centre. Department of Parasitology. RC Leiden, The Netherlands.Instituto Butantan. Centro de Biotecnologia. São Paulo, SP, Brasil.Aberystwyth University. Institute of Biological. Environmental and Rural Sciences. Aberystwyth, UK.Schistosoma mansoni venom allergen-like proteins (SmVALs) are part of a diverse protein superfamily partitioned into two groups (group 1 and group 2). Phylogenetic analyses of group 1 SmVALs revealed that members could be segregated into subclades (A-D); these subclades share similar gene expression patterns across the parasite lifecycle and immunological cross-reactivity. Furthermore, whole-mount in situ hybridization demonstrated that the phylogenetically, transcriptionally and immunologically-related SmVAL4, 10, 18 and 19 (subclade C) were all localized to the pre-acetabular glands of immature cercariae. Our results suggest that SmVAL group 1 phylogenetic relationships, stage-specific transcriptional profiles and tissue localization are predictive of immunological cross-reactivity

On the three-finger protein domain fold and CD59-like proteins in Schistosoma mansoni

Background: It is believed that schistosomes evade complement-mediated killing by expressing regulatory proteins on their surface. Recently, six homologues of human CD59, an important inhibitor of the complement system membrane attack complex, were identified in the schistosome genome. Therefore, it is important to investigate whether these molecules could act as CD59-like complement inhibitors in schistosomes as part of an immune evasion strategy. Methodology/Principal Findings: Herein, we describe the molecular characterization of seven putative SmCD59-like genes and attempt to address the putative biological function of two isoforms. Superimposition analysis of the 3D structure of hCD59 and schistosome sequences revealed that they contain the three-fingered protein domain (TFPD). However, the conserved amino acid residues involved in complement recognition in mammals could not be identified. Real-time RT-PCR and Western blot analysis determined that most of these genes are up-regulated in the transition from free-living cercaria to adult worm stage. Immunolocalization experiments and tegument preparations confirm that at least some of the SmCD59-like proteins are surface-localized; however, significant expression was also detected in internal tissues of adult worms. Finally, the involvement of two SmCD59 proteins in complement inhibition was evaluated by three different approaches: (i) a hemolytic assay using recombinant soluble forms expressed in Pichia pastoris and E. coli; (ii) complement-resistance of CHO cells expressing the respective membrane-anchored proteins; and (iii) the complement killing of schistosomula after gene suppression by RNAi. Our data indicated that these proteins are not involved in the regulation of complement activation. Conclusions: Our results suggest that this group of proteins belongs to the TFPD superfamily. Their expression is associated to intra-host stages, present in the tegument surface, and also in intra-parasite tissues. Three distinct approaches using SmCD59 proteins to inhibit complement strongly suggested that these proteins are not complement inhibitors and their function in schistosomes remains to be determined.Fundação de Amparo a Pesquisa do Estado de São Paulo (FAPESP, Grant Number:04/12872-3)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)National Institute of Health, National Institute of Allergy and Infectious Diseases (NIH-NIAID), Grant AI-095893NIH-NIAID Grant AI-056273FAPESP 00/11624-

Schistosoma mansoni Venom Allergen Like Proteins Present Differential Allergic Responses in a Murine Model of Airway Inflammation

The Schistosoma mansoni Venom Allergen Like proteins (SmVALs) have been identified in the Transcriptome and Post-Genomic studies as targets for immune interventions. Two secreted members of the family were obtained as recombinant proteins in the native conformation. Antibodies produced against them showed that SmVAL4 was present mostly in cercarial secretions and SmVAL26 in egg secretions and that only the native SmVAL4 contained carbohydrate moieties. Due to concerns with potential allergic characteristics of this class of molecules, we have explored the mouse model of airway inflammation in order to investigate these properties in a more confined system. Sensitization and challenge with rSmVAL4, but not rSmVAL26, induced extensive migration of cells to the lungs, mostly eosinophils and macrophages; moreover, immunological parameters were also characteristic of an allergic inflammatory response. Our results showed that the allergic potential of this class of proteins can be variable and that the vaccine candidates should be characterized; the mouse model of airway inflammation can be useful to evaluate these properties