Thirty-six Paralichthys patagonicus and 30 Xystreurys rasile were collected in the state of Rio de Janeiro, Brazil to investigate the presence of anisakid and raphidascaridid nematodes. Anisakis typica, Terranova sp., Contracaecum sp., Hysterothylacium deardorffoverstreetorum, and Raphidascaris sp. were identified using integrative taxonomy of morphological and genetic data. Morphological and morphometric analysis was conducted using bright field microscopy with scanning electron microscopy for topographic characterization of the cuticular surface. Phylogenetic analysis, using ITS and cox2 molecular targets, clearly demonstrated the species identification of A. typica and H. deardorffoverstreetorum and the high diversity of H. deardorffoverstreetorum. This is the first report of A. typica, H. deardorffoverstreetorum, and Raphidascaris sp. parasitizing P. patagonicus and X. rasile.
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http://dx.doi.org/10.1016/j.ijfoodmicro.2016.07.026 | DOI Listing |
Sci Rep
December 2024
College of Advanced Manufacturing Innovation, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand.
Vector-borne diseases pose a major worldwide health concern, impacting more than 1 billion people globally. Among various blood-feeding arthropods, mosquitoes stand out as the primary carriers of diseases significant in both medical and veterinary fields. Hence, comprehending their distinct role fulfilled by different mosquito types is crucial for efficiently addressing and enhancing control measures against mosquito-transmitted diseases.
View Article and Find Full Text PDFLithofacies classification and identification are of great significance in the exploration and evaluation of tight sandstone reservoirs. Existing methods of lithofacies identification in tight sandstone reservoirs face issues such as lengthy manual classification, strong subjectivity of identification, and insufficient sample datasets, which make it challenging to analyze the lithofacies characteristics of these reservoirs during oil and gas exploration. In this paper, the Fuyu oil formation in the Songliao Basin is selected as the target area, and an intelligent method for recognizing the lithophysics reservoirs in tight sandstone based on hybrid multilayer perceptron (MLP) and multivariate time series (MTS-Mixers) is proposed.
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December 2024
Negaunee Integrative Research Center, Field Museum, 1400 S. Dusable Lake Shore Drive, Chicago, IL, 60605, USA.
Enantiornithes are the most successful early-diverging avian clade, their fossils revealing important information regarding the structure of Cretaceous avifaunas and the parallel refinement of flight alongside the ornithuromorph lineage that includes modern birds. The most diverse recognized family of Early Cretaceous enantiornithines is the Bohaiornithidae, known from the Jehol Biota in northeastern China. Members of this clade enhance our understanding of intraclade morphological diversity and elucidate the independent evolution of this unique lineage.
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December 2024
Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran.
Surface electromyography (sEMG) data has been extensively utilized in deep learning algorithms for hand movement classification. This paper aims to introduce a novel method for hand gesture classification using sEMG data, addressing accuracy challenges seen in previous studies. We propose a U-Net architecture incorporating a MobileNetV2 encoder, enhanced by a novel Bidirectional Long Short-Term Memory (BiLSTM) and metaheuristic optimization for spatial feature extraction in hand gesture and motion recognition.
View Article and Find Full Text PDFExp Eye Res
December 2024
Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, 83 Fenyang Road, Shanghai, 200031, China; Key laboratory of Myopia and Related Eye Diseases, NHC, Chinese Academy of Medical Sciences, 83 Fenyang Road, Shanghai, 200031, China; Shanghai Key Laboratory of Visual Impairment and Restoration, 83 Fenyang Road, Shanghai, 200031, China. Electronic address:
Choroid neovascularization (CNV) is a distinct type of age-related macular degeneration (AMD) with a poor prognosis and responsible for the majority of vision loss in the elderly population. The laser-induced CNV model is a well-established animal model frequently used to study CNV. In this study, we performed an integrated analysis of metabolomic and transcriptomic data from CNV samples, utilizing multiple approaches including single-sample gene set enrichment analysis (ssGSEA), correlation analysis, and weighted gene co-expression network analysis (WGCNA), alongside various bioinformatics platforms, to identify key metabolic and immune signatures and to investigate their interplay during angiogenesis.
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