420 resultados para Shrimps - Classification - Molecular aspects


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Graphene has been reported with record-breaking properties which have opened up huge potential applications. A considerable research has been devoted to manipulate or modify the properties of graphene to target a more smart nanoscale device. Graphene and carbon nanotube hybrid structure (GNHS) is one of the promising graphene derivates, while their mechanical properties have been rarely discussed in literature. Therefore, such a studied is conducted in this paper basing on the large-scale molecular dynamics simulation. The target GNHS is constructed by considering two separate graphene layers that being connected by single-wall carbon nanotubes (SWCNTs) according to the experimental observations. It is found that the GNHSs exhibit a much lower yield strength, Young’s modulus, and earlier yielding comparing with a bilayer graphene sheet. Fracture of studied GNHSs is found to fracture located at the connecting region between carbon nanotubes (CNTs) and graphene. After failure, monatomic chains are normally observed at the front of the failure region, and the two graphene layers at the failure region without connecting CNTs will adhere to each other, generating a bilayer graphene sheet scheme (with a layer distance about 3.4 Å). This study will enrich the current understanding of the mechanical performance of GNHS, which will guide the design of GNHS and shed lights on its various applications.

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Enormous progress has been made towards understanding the role of specific factors in the process of epithelial-mesenchymal transition (EMT); however, the complex underlying pathways and the transient nature of the transition continues to present significant challenges. Targeting tumour cell plasticity underpinning EMT is an attractive strategy to combat metastasis. Global gene expression profiling and high-content analyses are among the strategies employed to identify novel EMT regulators. In this review, we highlight several approaches to systematically interrogate key pathways involved in EMT, with particular emphasis on the features of multiparametric, high-content imaging screening strategies that lend themselves to the systematic discovery of highly significant modulators of tumour cell plasticity.

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TCNQ·− radical anions (TCNQ = 7,7,8,8,-tetracyanoquinodimethane) form a wide range of semiconducting coordination polymers when coordinated to transition metals. Some such as CuTCNQ and AgTCNQ exhibit molecular switching and memory storage properties; others have intriguing magnetic properties and for example may behave as molecular magnets at low temperature. In this review, the electro- and photo-chemical synthesis and characterization of this important class of material is reviewed. In particular, the electrochemistry and the redox properties of TCNQ derivatives of coordination polymers based on Cu, Ag, Mn, Fe, Co, Ni, Zn and Cd transition metals are surveyed, with an emphasis on the mechanistic aspects of their electrochemical formation via nucleation–growth processes. Given that TCNQ is an extremely good electron acceptor, readily forming TCNQ•− and TCNQ2-, electrochemical reduction of TCNQ in the presence of a transition metal ion provides an ideal method for synthesis of metal-TCNQ materials by electrocrystallization from organic solvents and ionic liquids or solid-solid transformation using TCNQ modified electrodes from aqueous media containing transition metal electrolytes. The significance of the reversible formal potential (E0f) in these studies is discussed. The coupling of electrocrystallisation on electrode surfaces and microscopic characterization of the electrodeposited materials reveals a wide range of morphologies and phases which strongly influence their properties and applications. Since TCNQ also can be photo-reduced in the presence of suitable electron donors, analogous photochemical approaches to the synthesis of TCNQ-transition metal derivatives are available. The advantages of electrochemical and photochemical methods of synthesis relative to chemical synthesis are outlined.

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Cisplatin is one of the most potent anticancer agents, displaying significant clinical activity against a variety of solid tumours. To date, cisplatin-based combination treatment remains the most effective systemic chemotherapy for non-small cell lung cancer (NSCLC) patients. Unfortunately, the outcome of cisplatin therapy in NSCLC has reached a plateau due to the development of both intrinsic and acquired resistance that have become a major obstacle in the use of cisplatin in the clinical setting. The molecular mechanisms that underlie chemoresistance are largely unknown. Mechanisms of acquired resistance to cisplatin include reduced intracellular accumulation of the drug, enhanced drug inactivation by metallothionine and glutathione, increased repair activity of DNA damage, and altered expression of oncogenes and regulatory proteins. Cisplatin-induced cytotoxicity is mediated through the induction of apoptosis and cell cycle arrest as a result of cisplatin-DNA adduct formation, which in turn, activates multiple signaling pathways and mediators. These include p53, Bcl-2 family, caspases, cyclins, CDKs, MAPK and PI3K/Akt. Increased expression of anti-apoptotic genes and mutations in the intrinsic apoptotic pathway may also contribute to the inability of cells to detect DNA damage or to induce apoptosis. This chapter will provide an insight into the mechanisms involved in cisplatin resistance and a better understanding of the molecular basis of the cellular response to cisplatin-based chemotherapy in lung cancer.

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Object classification is plagued by the issue of session variation. Session variation describes any variation that makes one instance of an object look different to another, for instance due to pose or illumination variation. Recent work in the challenging task of face verification has shown that session variability modelling provides a mechanism to overcome some of these limitations. However, for computer vision purposes, it has only been applied in the limited setting of face verification. In this paper we propose a local region based intersession variability (ISV) modelling approach, and apply it to challenging real-world data. We propose a region based session variability modelling approach so that local session variations can be modelled, termed Local ISV. We then demonstrate the efficacy of this technique on a challenging real-world fish image database which includes images taken underwater, providing significant real-world session variations. This Local ISV approach provides a relative performance improvement of, on average, 23% on the challenging MOBIO, Multi-PIE and SCface face databases. It also provides a relative performance improvement of 35% on our challenging fish image dataset.

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Chlamydia trachomatis is the most common sexually transmitted bacterial infection worldwide. The impact of this pathogen on human reproduction has intensified research efforts to better understand chlamydial infection and pathogenesis. Whilst there are animal models available that mimic the many aspects of human chlamydial infection, the mouse is regarded as the most practical and widely used of the models. Studies in mice have greatly contributed to our understanding of the host-pathogen interaction and provided an excellent medium for evaluating vaccines. Here we explore the advantages and disadvantages of all animal models of chlamydial genital tract infection, with a focus on the murine model and what we have learnt from it so far.

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Dermal wound repair involves complex interactions between cells, cytokines and mechanics to close injuries to the skin. In particular, we investigate the contribution of fibroblasts, myofibroblasts, TGFβ, collagen and local tissue mechanics to wound repair in the human dermis. We develop a morphoelastic model where a realistic representation of tissue mechanics is key, and a fibrocontractive model that involves a reasonable approximation to the true kinetics of the important bioactive species. We use each of these descriptions to elucidate the mechanisms that generate pathologies such as hypertrophic scars, contractures and keloids. We find that for hypertrophic scar and contracture development, factors regulating the myofibroblast phenotype are critical, with heightened myofibroblast activation, reduced myofibroblast apoptosis or prolonged inflammation all predicted as mediators for scar hypertrophy and contractures. Prevention of these pathologies is predicted when myofibroblast apoptosis is induced, myofibroblast activation is blocked or TGFβ is neutralised. To investigate keloid invasion, we develop a caricature representation of the fibrocontractive model and find that TGFβ spread is the driving factor behind keloid growth. Blocking activation of TGFβ is found to cause keloid regression. Thus, we recommend myofibroblasts and TGFβ as targets for clinicians when developing intervention strategies for prevention and cure of fibrotic scars.

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Three cohorts of farmed yellowtail kingfish (Seriola lalandi) from South Australia were examined for Chlamydia-like organisms associated with epitheliocystis. To characterize the bacteria, 38 gill samples were processed for histopathology, electron microscopy, and 16S rRNA amplification, sequencing, and phylogenetic analysis. Microscopically, the presence of membrane-enclosed cysts was observed within the gill lamellae. Also observed was hyperplasia of the epithelial cells with cytoplasmic vacuolization and fusion of the gill lamellae. Transmission electron microscopy revealed morphological features of the reticulate and intermediate bodies typical of members of the order Chlamydiales. A novel 1,393-bp 16S chlamydial rRNA sequence was amplified from gill DNA extracted from fish in all cohorts over a 3-year period that corresponded to the 16S rRNA sequence amplified directly from laser-dissected cysts. This sequence was only 87% similar to the reported "Candidatus Piscichlamydia salmonis" (AY462244) from Atlantic salmon and Arctic charr. Phylogenetic analysis of this sequence against 35 Chlamydia and Chlamydia-like bacteria revealed that this novel bacterium belongs to an undescribed family lineage in the order Chlamydiales. Based on these observations, we propose this bacterium of yellowtail kingfish be known as "Candidatus Parilichlamydia carangidicola" and that the new family be known as "Candidatus Parilichlamydiaceae."

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Histological analysis of gill samples taken from individuals of Latris lineata reared in aquaculture in Tasmania, Australia, and those sampled from the wild revealed the presence of epitheliocystis-like basophilic inclusions. Subsequent morphological, in situ hybridization, and molecular analyses were performed to confirm the presence of this disease and discovered a Chlamydia-like organism associated with this condition, and the criteria set by Fredericks and Relman's postulates were used to establish disease causation. Three distinct 16S rRNA genotypes were sequenced from 16 fish, and phylogenetic analyses of the nearly full-length 16S rRNA sequences generated for this bacterial agent indicated that they were nearly identical novel members of the order Chlamydiales. This new taxon formed a well-supported clade with "Candidatus Parilichlamydia carangidicola" from the yellowtail kingfish (Seriola lalandi). On the basis of sequence divergence over the 16S rRNA region relative to all other members of the order Chlamydiales, a new genus and species are proposed here for the Chlamydia-like bacterium from L. lineata, i.e., "Candidatus Similichlamydia latridicola" gen. nov., sp. nov.

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Chlamydia pecorum is a significant pathogen of domestic livestock and wildlife. We have developed a C. pecorum-specific multilocus sequence analysis (MLSA) scheme to examine the genetic diversity of and relationships between Australian sheep, cattle, and koala isolates. An MLSA of seven concatenated housekeeping gene fragments was performed using 35 isolates, including 18 livestock isolates (11 Australian sheep, one Australian cow, and six U.S. livestock isolates) and 17 Australian koala isolates. Phylogenetic analyses showed that the koala isolates formed a distinct clade, with limited clustering with C. pecorum isolates from Australian sheep. We identified 11 MLSA sequence types (STs) among Australian C. pecorum isolates, 10 of them novel, with koala and sheep sharing at least one identical ST (designated ST2013Aa). ST23, previously identified in global C. pecorum livestock isolates, was observed here in a subset of Australian bovine and sheep isolates. Most notably, ST23 was found in association with multiple disease states and hosts, providing insights into the transmission of this pathogen between livestock hosts. The complexity of the epidemiology of this disease was further highlighted by the observation that at least two examples of sheep were infected with different C. pecorum STs in the eyes and gastrointestinal tract. We have demonstrated the feasibility of our MLSA scheme for understanding the host relationship that exists between Australian C. pecorum strains and provide the first molecular epidemiological data on infections in Australian livestock hosts.

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A cell classification algorithm that uses first, second and third order statistics of pixel intensity distributions over pre-defined regions is implemented and evaluated. A cell image is segmented into 6 regions extending from a boundary layer to an inner circle. First, second and third order statistical features are extracted from histograms of pixel intensities in these regions. Third order statistical features used are one-dimensional bispectral invariants. 108 features were considered as candidates for Adaboost based fusion. The best 10 stage fused classifier was selected for each class and a decision tree constructed for the 6-class problem. The classifier is robust, accurate and fast by design.

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Real-time image analysis and classification onboard robotic marine vehicles, such as AUVs, is a key step in the realisation of adaptive mission planning for large-scale habitat mapping in previously unexplored environments. This paper describes a novel technique to train, process, and classify images collected onboard an AUV used in relatively shallow waters with poor visibility and non-uniform lighting. The approach utilises Förstner feature detectors and Laws texture energy masks for image characterisation, and a bag of words approach for feature recognition. To improve classification performance we propose a usefulness gain to learn the importance of each histogram component for each class. Experimental results illustrate the performance of the system in characterisation of a variety of marine habitats and its ability to operate onboard an AUV's main processor suitable for real-time mission planning.