928 resultados para MOLECULAR-DETECTION
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Despite their ecological significance as decomposers and their evolutionary significance as the most speciose eusocial insect group outside the Hymenoptera, termite (Blattodea: Termitoidae or Isoptera) evolutionary relationships have yet to be well resolved. Previous morphological and molecular analyses strongly conflict at the family level and are marked by poor support for backbone nodes. A mitochondrial (mt) genome phylogeny of termites was produced to test relationships between the recognised termite families, improve nodal support and test the phylogenetic utility of rare genomic changes found in the termite mt genome. Complete mt genomes were sequenced for 7 of the 9 extant termite families with additional representatives of each of the two most speciose families Rhinotermitidae (3 of 7 subfamilies) and Termitidae (3 of 8 subfamilies). The mt genome of the well supported sister group of termites, the subsocial cockroach Cryptocercus, was also sequenced. A highly supported tree of termite relationships was produced by all analytical methods and data treatment approaches, however the relationship of the termites + Cryptocercus clade to other cockroach lineages was highly affected by the strong nucleotide compositional bias found in termites relative to other dictyopterans. The phylogeny supports previously proposed suprafamilial termite lineages, the Euisoptera and Neoisoptera, a later derived Kalotermitidae as sister group of the Neoisoptera and a monophyletic clade of dampwood (Stolotermitidae, Archotermopsidae) and harvester termites (Hodotermitidae). In contrast to previous termite phylogenetic studies, nodal supports were very high for family-level relationships within termites. Two rare genomic changes in the mt genome control region were found to be molecular synapomorphies for major clades. An elongated stem-loop structure defined the clade Polyphagidae + (Cryptocercus + termites), and a further series of compensatory base changes in this stem loop is synapomorphic for the Neoisoptera. The complicated repeat structures first identified in Reticulitermes, composed of short (A-type) and long (B-type repeats) defines the clade Heterotermitinae + Termitidae, while the secondary loss of A-type repeats is synapomorphic for the non-macrotermitine Termitidae.
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1. Local extinctions in habitat patches and asymmetric dispersal between patches are key processes structuring animal populations in heterogeneous environments. Effective landscape conservation requires an understanding of how habitat loss and fragmentation influence demographic processes within populations and movement between populations. 2. We used patch occupancy surveys and molecular data for a rainforest bird, the logrunner (Orthonyx temminckii), to determine (i) the effects of landscape change and patch structure on local extinction; (ii) the asymmetry of emigration and immigration rates; (iii) the relative influence of local and between-population landscapes on asymmetric emigration and immigration; and (iv) the relative contributions of habitat loss and habitat fragmentation to asymmetric emigration and immigration. 3. Whether or not a patch was occupied by logrunners was primarily determined by the isolation of that patch. After controlling for patch isolation, patch occupancy declined in landscapes experiencing high levels of rainforest loss over the last 100 years. Habitat loss and fragmentation over the last century was more important than the current pattern of patch isolation alone, which suggested that immigration from neighbouring patches was unable to prevent local extinction in highly modified landscapes. 4. We discovered that dispersal between logrunner populations is highly asymmetric. Emigration rates were 39% lower when local landscapes were fragmented, but emigration was not limited by the structure of the between-population landscapes. In contrast, immigration was 37% greater when local landscapes were fragmented and was lower when the between-population landscapes were fragmented. Rainforest fragmentation influenced asymmetric dispersal to a greater extent than did rainforest loss, and a 60% reduction in mean patch area was capable of switching a population from being a net exporter to a net importer of dispersing logrunners. 5. The synergistic effects of landscape change on species occurrence and asymmetric dispersal have important implications for conservation. Conservation measures that maintain large patch sizes in the landscape may promote asymmetric dispersal from intact to fragmented landscapes and allow rainforest bird populations to persist in fragmented and degraded landscapes. These sink populations could form the kernel of source populations given sufficient habitat restoration. However, the success of this rescue effect will depend on the quality of the between-population landscapes.
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Purpose: To investigate the correlations of the global flash multifocal electroretinogram (MOFO mfERG) with common clinical visual assessments – Humphrey perimetry and Stratus circumpapillary retinal nerve fiber layer (RNFL) thickness measurement in type II diabetic patients. Methods: Forty-two diabetic patients participated in the study: ten were free from diabetic retinopathy (DR) while the remainder suffered from mild to moderate non-proliferative diabetic retinopathy (NPDR). Fourteen age-matched controls were recruited for comparison. MOFO mfERG measurements were made under high and low contrast conditions. Humphrey central 30-2 perimetry and Stratus OCT circumpapillary RNFL thickness measurements were also performed. Correlations between local values of implicit time and amplitude of the mfERG components (direct component (DC) and induced component (IC)), and perimetric sensitivity and RNFL thickness were evaluated by mapping the localized responses for the three subject groups. Results: MOFO mfERG was superior to perimetry and RNFL assessments in showing differences between the diabetic groups (with and without DR) and the controls. All the MOFO mfERG amplitudes (except IC amplitude at high contrast) correlated better with perimetry findings (Pearson’s r ranged from 0.23 to 0.36, p<0.01) than did the mfERG implicit time at both high and low contrasts across all subject groups. No consistent correlation was found between the mfERG and RNFL assessments for any group or contrast conditions. The responses of the local MOFO mfERG correlated with local perimetric sensitivity but not with RNFL thickness. Conclusion: Early functional changes in the diabetic retina seem to occur before morphological changes in the RNFL.
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The increasingly widespread use of large-scale 3D virtual environments has translated into an increasing effort required from designers, developers and testers. While considerable research has been conducted into assisting the design of virtual world content and mechanics, to date, only limited contributions have been made regarding the automatic testing of the underpinning graphics software and hardware. In the work presented in this paper, two novel neural network-based approaches are presented to predict the correct visualization of 3D content. Multilayer perceptrons and self-organizing maps are trained to learn the normal geometric and color appearance of objects from validated frames and then used to detect novel or anomalous renderings in new images. Our approach is general, for the appearance of the object is learned rather than explicitly represented. Experiments were conducted on a game engine to determine the applicability and effectiveness of our algorithms. The results show that the neural network technology can be effectively used to address the problem of automatic and reliable visual testing of 3D virtual environments.
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The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.
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In this paper we present a fast power line detection and localisation algorithm as well as propose a high-level guidance architecture for active vision-based Unmanned Aerial Vehicle (UAV) guidance. The detection stage is based on steerable filters for edge ridge detection, followed by a line fitting algorithm to refine candidate power lines in images. The guidance architecture assumes an UAV with an onboard Gimbal camera. We first control the position of the Gimbal such that the power line is in the field of view of the camera. Then its pose is used to generate the appropriate control commands such that the aircraft moves and flies above the lines. We present initial experimental results for the detection stage which shows that the proposed algorithm outperforms two state-of-the-art line detection algorithms for power line detection from aerial imagery.
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Background: The regulation of plasminogen activation is a key element in controlling proteolytic events in the extracellular matrix. Our previous studies had demonstrated that in inflamed gingival tissues, tissue-type plasminogen activator (t-PA) is significantly increased in the extracellular matrix of the connective tissue and that interleukin 1β (IL-1β) can up regulate the level of t-PA and plasminogen activator inhibitor-2 (PAI-2) synthesis by human gingival fibroblasts. Method: In the present study, the levels of t-PA and PAI-2 in gingival crevicular fluid (GCF) were measured from healthy, gingivitis and periodontitis sites and compared before and after periodontal treatment. Crevicular fluid from106 periodontal sites in 33 patients were collected. 24 sites from 11 periodontitis patients received periodontal treatment after the first sample collection and post-treatment samples were collected 14 days after treatment. All samples were analyzed by enzyme-linked immunosorbent assay (ELISA) for t-PA and PAI-2. Results: The results showed that significantly high levels of t-PA and PAI-2 in GCF were found in the gingivitis and periodontitis sites. Periodontal treatment led to significant decreases of PAI-2, but not t-PA, after 14 days. A significant positive linear correlation was found between t-PA and PAI-2 in GCF (r=0.80, p<0.01). In the healthy group, different sites from within the same subject showed little variation of t-PA and PAI-2 in GCF. However, the gingivitis and periodontitis sites showed large variation. These results suggest a good correlation between t-PA and PAI-2 with the severity of periodontal conditions. Conclusion: This study indicates that t-PA and PAI-2 may play a significant rôle in the periodontal tissue destruction and tissue remodeling and that t-PA and PAI-2 in GCF may be used as clinical markers to evaluate the periodontal diseases and assess treatment.
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BACKGROUND: Demineralized freeze-dried bone allografts (DFDBAs) have been proposed as a useful adjunct in periodontal therapy to induce periodontal regeneration through the induction of new bone formation. The presence of bone morphogenetic proteins (BMPs) within the demineralized matrix has been proposed as a possible mechanism through which DFDBA may exert its biologic effect. However, in recent years, the predictability of results using DFDBA has been variable and has led to its use being questioned. One reason for the variability in tissue response may be attributed to differences in the processing of DFDBA, which may lead to loss of activity of any bioactive substances within the DFDBA matrix. Therefore, the purpose of this investigation was to determine whether there are detectable levels of bone morphogenetic proteins in commercial DFDBA preparations. METHODS: A single preparation of DFDBA was obtained from three commercial sources. Each preparation was studied in triplicate. Proteins within the DFDBA samples were first extracted with 4M guanidinium HCI for seven days at 40 degrees celsius and the residue was further extracted with 4M guanidinium HCL/EDTA for seven days at 40 degrees celsius. Two anti-human BMP-2 and -4 antibodies were used for the detection of the presence of BMP's in the extracts. RESULTS: Neither BMP-2 nor BMP-4 was detected in any of the extracts. When recombinant human BMP-2 and -4 were added throughout the extraction process of DFDBA extraction, not only were intact proteins detected but smaller molecular weight fragments were also noted in the extract. CONCLUSIONS: These results indicate that all of the DFDBA samples tested had no detectable amounts of BMP-2 and -4. In addition, an unknown substance present in the DFDBA may be responsible for degradation of whatever BMPs might be present.
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The increasing popularity of video consumption from mobile devices requires an effective video coding strategy. To overcome diverse communication networks, video services often need to maintain sustainable quality when the available bandwidth is limited. One of the strategy for a visually-optimised video adaptation is by implementing a region-of-interest (ROI) based scalability, whereby important regions can be encoded at a higher quality while maintaining sufficient quality for the rest of the frame. The result is an improved perceived quality at the same bit rate as normal encoding, which is particularly obvious at the range of lower bit rate. However, because of the difficulties of predicting region-of-interest (ROI) accurately, there is a limited research and development of ROI-based video coding for general videos. In this paper, the phase spectrum quaternion of Fourier Transform (PQFT) method is adopted to determine the ROI. To improve the results of ROI detection, the saliency map from the PQFT is augmented with maps created from high level knowledge of factors that are known to attract human attention. Hence, maps that locate faces and emphasise the centre of the screen are used in combination with the saliency map to determine the ROI. The contribution of this paper lies on the automatic ROI detection technique for coding a low bit rate videos which include the ROI prioritisation technique to give different level of encoding qualities for multiple ROIs, and the evaluation of the proposed automatic ROI detection that is shown to have a close performance to human ROI, based on the eye fixation data.
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The application of nanotechnology products has increased significantly in recent years. With their broad range of applications, including electronics, food and agriculture, power and energy, scientific instruments, clothing, cosmetics, buildings, biomedical and health, etc (Catanzariti, 2008), nanomaterials are an indispensible part of human life.
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Complexes of the type \[M(phen)3](PF6)2 (M = Ni(II), Fe(II), Ru(II) and phen = 1,10-phenanthroline) were found to co-crystallize to form molecular alloys (solid solutions of molecules) with general formula \[MAxMB1–x(phen)3](PF6)2·0.5H2O in which the relative concentrations of the metal complexes in the crystals closely match those in the crystallizing solution. Consequently, the composition of the co-crystals can be accurately predicted and controlled by modulating the relative concentrations of the metal complexes in the crystallizing solution. Although they are chemically and structurally similar, complexes of the type \[M(bipy)3](PF6)2 (M = Ni(II), Fe(II), Ru(II) and bipy = 2,2′-bipyridine) display markedly different behavior upon co-crystallization. In this case, the resulting co-crystals of general formula \[MAxMB1–x(bipy)3](PF6)2 have relative concentrations of the constituent complexes that are markedly different from the relative concentrations of the complexes initially present in the crystallizing solution. For example, when the nickel and iron complexes are co-crystallized from a solution containing a 50:50 ratio of each, the result is the formation of some crystals with a higher proportion of iron and others with a higher proportion of nickel. The relative concentrations of the metal complexes in the crystals can vary from those in the crystallizing solutions by as much as 15%. This result was observed for a range of combinations of metal complexes (Ni/Fe, Ni/Ru, and Fe/Ru) and a range of starting concentrations in the crystallizing solutions (90:10 through to 10:90 in 10% increments). To explain this remarkable result, we introduce the concept of “supramolecular selection”, which is a process driven by molecular recognition that leads to the partially selective aggregation of like molecules during crystallization.
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Members of the Calliphoridae (blowflies) are significant for medical and veterinary management, due to the ability of some species to consume living flesh as larvae, and for forensic investigations due to the ability of others to develop in corpses. Due to the difficulty of accurately identifying larval blowflies to species there is a need for DNA-based diagnostics for this family, however the widely used DNA-barcoding marker, cox1, has been shown to fail for several groups within this family. Additionally, many phylogenetic relationships within the Calliphoridae are still unresolved, particularly deeper level relationships. Sequencing whole mt genomes has been demonstrated both as an effective method for identifying the most informative diagnostic markers and for resolving phylogenetic relationships. Twenty-seven complete, or nearly so, mt genomes were sequenced representing 13 species, seven genera and four calliphorid subfamilies and a member of the related family Tachinidae. PCR and sequencing primers developed for sequencing one calliphorid species could be reused to sequence related species within the same superfamily with success rates ranging from 61% to 100%, demonstrating the speed and efficiency with which an mt genome dataset can be assembled. Comparison of molecular divergences for each of the 13 protein-coding genes and 2 ribosomal RNA genes, at a range of taxonomic scales identified novel targets for developing as diagnostic markers which were 117–200% more variable than the markers which have been used previously in calliphorids. Phylogenetic analysis of whole mt genome sequences resulted in much stronger support for family and subfamily-level relationships. The Calliphoridae are polyphyletic, with the Polleninae more closely related to the Tachinidae, and the Sarcophagidae are the sister group of the remaining calliphorids. Within the Calliphoridae, there was strong support for the monophyly of the Chrysomyinae and Luciliinae and for the sister-grouping of Luciliinae with Calliphorinae. Relationships within Chrysomya were not well resolved. Whole mt genome data, supported the previously demonstrated paraphyly of Lucilia cuprina with respect to L. sericata and allowed us to conclude that it is due to hybrid introgression prior to the last common ancestor of modern sericata populations, rather than due to recent hybridisation, nuclear pseudogenes or incomplete lineage sorting.
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Background: Right-to-left shunting via a patent foramen ovale (PFO) has a recognized association with embolic events in younger patients. The use of agitated saline contrast imaging (ASCi) for detecting atrial shunting is well documented, however optimal technique is not well described. The purpose of this study is to assess the efficacy and safety of ASCi via TTE for assessment of right-to-left atrial communication in a large cohort of patients. Method: A retrospective review was undertaken of 1162 consecutive transthoracic (TTE) ASCi studies, of which 195 had also undergone clinically indicated transesophageal (TEE) echo. ASCi shunt results were compared with color flow imaging (CFI) and the role of provocative maneuvers (PM) assessed. Results: 403 TTE studies (35%) had paradoxical shunting seen during ASCi. Of these, 48% were positive with PM only. There was strong agreement between TTE ASCi and reported TEE findings (99% sensitivity, 85% specificity), with six false positive and two false negative results. In hindsight, the latter were likely due to suboptimal right atrial opacification, and the former due to transpulmonary shunting. TTE CFI was found to be insensitive (22%) for the detection of a PFO compared with TTE ASCi. Conclusions: TTE ASCi is minimally invasive and highly accurate for the detection of right-to-left atrial communication when PM are used. TTE CFI was found to be insensitive for PFO screening. It is recommended that TTE ASCi should be considered the initial diagnostic tool for the detection of PFO in clinical practice. A dedicated protocol should be followed to ensure adequate agitated saline contrast delivery and performance of provocative maneuvers.
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This work-in-progress paper presents an ensemble-based model for detecting and mitigating Distributed Denial-of-Service (DDoS) attacks, and its partial implementation. The model utilises network traffic analysis and MIB (Management Information Base) server load analysis features for detecting a wide range of network and application layer DDoS attacks and distinguishing them from Flash Events. The proposed model will be evaluated against realistic synthetic network traffic generated using a software-based traffic generator that we have developed as part of this research. In this paper, we summarise our previous work, highlight the current work being undertaken along with preliminary results obtained and outline the future directions of our work.
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Cognitive radio is an emerging technology proposing the concept of dynamic spec- trum access as a solution to the looming problem of spectrum scarcity caused by the growth in wireless communication systems. Under the proposed concept, non- licensed, secondary users (SU) can access spectrum owned by licensed, primary users (PU) so long as interference to PU are kept minimal. Spectrum sensing is a crucial task in cognitive radio whereby the SU senses the spectrum to detect the presence or absence of any PU signal. Conventional spectrum sensing assumes the PU signal as ‘stationary’ and remains in the same activity state during the sensing cycle, while an emerging trend models PU as ‘non-stationary’ and undergoes state changes. Existing studies have focused on non-stationary PU during the transmission period, however very little research considered the impact on spectrum sensing when the PU is non-stationary during the sensing period. The concept of PU duty cycle is developed as a tool to analyse the performance of spectrum sensing detectors when detecting non-stationary PU signals. New detectors are also proposed to optimise detection with respect to duty cycle ex- hibited by the PU. This research consists of two major investigations. The first stage investigates the impact of duty cycle on the performance of existing detec- tors and the extent of the problem in existing studies. The second stage develops new detection models and frameworks to ensure the integrity of spectrum sensing when detecting non-stationary PU signals. The first investigation demonstrates that conventional signal model formulated for stationary PU does not accurately reflect the behaviour of a non-stationary PU. Therefore the performance calculated and assumed to be achievable by the conventional detector does not reflect actual performance achieved. Through analysing the statistical properties of duty cycle, performance degradation is proved to be a problem that cannot be easily neglected in existing sensing studies when PU is modelled as non-stationary. The second investigation presents detectors that are aware of the duty cycle ex- hibited by a non-stationary PU. A two stage detection model is proposed to improve the detection performance and robustness to changes in duty cycle. This detector is most suitable for applications that require long sensing periods. A second detector, the duty cycle based energy detector is formulated by integrat- ing the distribution of duty cycle into the test statistic of the energy detector and suitable for short sensing periods. The decision threshold is optimised with respect to the traffic model of the PU, hence the proposed detector can calculate average detection performance that reflect realistic results. A detection framework for the application of spectrum sensing optimisation is proposed to provide clear guidance on the constraints on sensing and detection model. Following this framework will ensure the signal model accurately reflects practical behaviour while the detection model implemented is also suitable for the desired detection assumption. Based on this framework, a spectrum sensing optimisation algorithm is further developed to maximise the sensing efficiency for non-stationary PU. New optimisation constraints are derived to account for any PU state changes within the sensing cycle while implementing the proposed duty cycle based detector.