Sequence analysis of the second internal Transcribed spacer (ITS2) region of rDNA for species identification of trichostrongylus nematodes isolated from domestic livestock in Iran

Background: Infectivity of herbivores with Trichostrongylus nematodes is widespread in many countries, having a major economic impact on breeding, survivability, and productivity of domestic livestock. This study was carried out on Trichostrongylus species isolated from domestic livestock in order to develop an easy-to-perform method for species identification. Methods: Trichostrongylus isolates were collected from sheep, goat, cattle, and buffaloes in Khuzestan Province, southwest Iran. Primary species identification was carried out based on morphological characterization of male worms. PCR amplification of ITS2-rDNA region was performed on genomic DNA and the products were sequenced. Phylogenetic analysis of the nucleotide sequence data was conducted employing Bayesian Inference approach. Consequently, a restriction fragment length polymorphism (RFLP) profile was designed to differentiate Trichostrongylus species. Results: A consensus sequence of 238 nucleotides was deposited in the GenBank for Iranian isolates of Trichostrongylus species including T. colubriformis, T. capricola, T. probolurus and T. vitrinus. The designated RFLP using restriction enzyme TasI could readily differentiate among species having different ITS2 sequence. The molecular analysis was in concordance with morphological findings. Conclusion: Phylogenetic analysis indicated a close relationship among the sequences obtained in this study and reference sequence of relevant species. ITS2-RFLP with TasI is recommended for molecular differentiation of common Trichostrongylus species

Genetic variability of Taenia saginata inferred from mitochondrial DNA sequences

Taenia saginata is an important tapeworm, infecting humans in many parts of the world. The present study was undertaken to identify inter- and intraspecific variation of T. saginata isolated from cattle in different parts of Iran using two mitochondrial CO1 and 12S rRNA genes. Up to 105 bovine specimens of T. saginata were collected from 20 slaughterhouses in three provinces of Iran. DNA were extracted from the metacestode Cysticercus bovis. After PCR amplification, sequencing of CO1 and 12S rRNA genes were carried out and two phylogenetic analyses of the sequence data were generated by Bayesian inference on CO1 and 12S rRNA sequences. Sequence analyses of CO1 and 12S rRNA genes showed 11 and 29 representative profiles respectively. The level of pairwise nucleotide variation between individual haplotypes of CO1 gene was 0.3–2.4 % while the overall nucleotide variation among all 11 haplotypes was 4.6 %. For 12S rRNA sequence data, level of pairwise nucleotide variation was 0.2–2.5 % and the overall nucleotide variation was determined as 5.8 % among 29 haplotypes of 12S rRNA gene. Considerable genetic diversity was found in both mitochondrial genes particularly in 12S rRNA gene. © 2015, Springer-Verlag Berlin Heidelberg

Discrete alpha-skew-Laplace Distribution

Classical discrete distributions rarely support modelling data on the set of whole integers. In this paper, we shall introduce a flexible discrete distribution on this set, which can, in addition, cover bimodal as well as unimodal data sets. The proposed distribution can also be fitted to positive and negative skewed data. The distribution is indeed a discrete counterpart of the continuous alpha-skew-Laplace distribution recently introduced in the literature. The proposed distribution can also be viewed as a weighted version of the discrete Laplace distribution. Several distributional properties of this class such as cumulative distribution function, moment generating function, moments, modality, infinite divisibility and its truncation are studied. A simulation study is also performed. Finally, a real data set is used to show applicability of the new model comparing to several rival models, such as the discrete normal and Skellam distributions

Distribution-Matching Embedding for Visual Domain Adaptation

Domain-invariant representations are key to addressing the domain shift problem where the training and test examples follow different distributions. Existing techniques that have attempted to match the distributions of the source and target domains typically compare these distributions in the original feature space. This space, however, may not be directly suitable for such a comparison, since some of the features may have been distorted by the domain shift, or may be domain specific. In this paper, we introduce a Distribution-Matching Embedding approach: An unsupervised domain adaptation method that overcomes this issue by mapping the data to a latent space where the distance between the empirical distributions of the source and target examples is minimized. In other words, we seek to extract the information that is invariant across the source and target data. In particular, we study two different distances to compare the source and target distributions: the Maximum Mean Discrepancy and the Hellinger distance. Furthermore, we show that our approach allows us to learn either a linear embedding, or a nonlinear one. We demonstrate the benefits of our approach on the tasks of visual object recognition, text categorization, and WiFi localization

Statistically Motivated Second Order Pooling

Second-order pooling, a.k.a.~bilinear pooling, has proven effective for deep learning based visual recognition. However, the resulting second-order networks yield a final representation that is orders of magnitude larger than that of standard, first-order ones, making them memory-intensive and cumbersome to deploy. Here, we introduce a general, parametric compression strategy that can produce more compact representations than existing compression techniques, yet outperform both compressed and uncompressed second-order models. Our approach is motivated by a statistical analysis of the network's activations, relying on operations that lead to a Gaussian-distributed final representation, as inherently used by first-order deep networks. As evidenced by our experiments, this lets us outperform the state-of-the-art first-order and second-order models on several benchmark recognition datasets.Comment: Accepted to ECCV 2018. Camera ready version. 14 page, 5 figures, 3 table

Solution to IDA-PBC PDEs by Pfaffian Differential Equations

Finding the general solution of partial differential equations (PDEs) is essential for controller design in some methods. Interconnection and damping assignment passivity based control (IDA-PBC) is one of such methods in which the solution to corresponding PDEs is needed to apply it in practice. In this paper, such PDEs are transformed to corresponding Pfaffian differential equations. Furthermore, it is shown that upon satisfaction of the integrability condition, the solution to the corresponding third order Pfaffian differential equation may be obtained quite easily. The method is applied to the PDEs of IDA-PBC in some benchmark problems such as Magnetic levitation system, Pendubot and underactuated cable driven robot to verify its applicability

Molecular signatures of a TLR4 agonist-adjuvanted HIV-1 vaccine candidate in humans

Systems biology approaches have recently provided new insights into the mechanisms of action of human vaccines and adjuvants. Here, we investigated early transcriptional signatures induced in whole blood of healthy subjects following vaccination with a recombinant HIV-1 envelope glycoprotein subunit CN54gp140 adjuvanted with the TLR4 agonist glucopyranosyl lipid adjuvant-aqueous formulation (GLA-AF) and correlated signatures to CN54gp140-specific serum antibody responses. Fourteen healthy volunteers aged 18-45 years were immunized intramuscularly three times at 1-month intervals and whole blood samples were collected at baseline, 6 h, and 1, 3, and 7 days post first immunization. Subtle changes in the transcriptomic profiles were observed following immunization, ranging from over 300 differentially expressed genes (DEGs) at day 1 to nearly 100 DEGs at day 7 following immunization. Functional pathway analysis revealed blood transcription modules (BTMs) related to general cell cycle activation, and innate immune cell activation at early time points, as well as BTMs related to T cells and B cell activation at the later time points post-immunization. Diverse CN54gp140-specific serum antibody responses of the subjects enabled their categorization into high or low responders, at early ( < 1 month) and late (up to 6 months) time points post vaccination. BTM analyses revealed repression of modules enriched in NK cells, and the mitochondrial electron chain, in individuals with high or sustained antigen-specific antibody responses. However, low responders showed an enhancement of BTMs associated with enrichment in myeloid cells and monocytes as well as integrin cell surface interactions. Flow cytometry analysis of peripheral blood mononuclear cells obtained from the subjects revealed an enhanced frequency of CD56 dim NK cells in the majority of vaccines 14 days after vaccination as compared with the baseline. These results emphasize the utility of a systems biology approach to enhance our understanding on the mechanisms of action of TLR4 adjuvanted human vaccines

Genotyping Echinococcus granulosus from dogs from Western Iran

Cystic echinococcosis is a zoonotic infection caused by the dog tapeworm, Echinococcus granulosus. In the present study, adults of E. granulosus (n = 20) were collected from 71 dogs from Western Iran and were genetically characterized using DNA sequencing of the partial mitochondrial cytochrome c oxidase subunit 1 (cox1) and NADH dehydrogenase 1 (nad1). Consensus sequences were obtained for cox1 (366) and nad1 (471) genes. Phylogenetic analysis of concatenated nad1 and cox1 nucleotide sequence data was performed using Bayesian Inference approach. Overall, the dog isolates indicated nine different sequences in cox1 and seven in nad1 genes. Three genotypes (G1 [75%], G2 [10%] and G3 [15%]) were identified from the isolates. The G2 sequences indicated 100% homology with reference G2 sequence in both cox1 (Genbank accession number M84662) and nad1 (AJ237633) genes. G3 sequences showed 100% homology with G3 reference sequence in nad1 (AJ237633), but displayed two different cox1 profiles, each having 99% homology with reference G3 sequence (M84663). In the phylogenetic tree all of the isolates were grouped into a distinct cluster corresponding to the G1-G3 complex with relevant reference sequences. The presence of G1 genotype (sheep strain) of E. granulosus sensu stricto as dominant genotype in dogs is emphasized. To the best of our knowledge, this study established the first record of E. granulosus sensu stricto, G2 genotype in Iran. © 2012 Elsevier Inc