928 resultados para Non-structural Protein Ns2a And Ns3
Resumo:
Increasing ethnic diversity in the UK means that there is a growing need for National Health Service care to be delivered to non-English-speaking patients. The aims of the present systematic review were to: (1) better understand the outcomes of chronic pain management programmes (PMPs) for ethnic minority and non-English-speaking patients and (2) explore the perspectives on and experiences of chronic pain for these groups. A systematic review identified 26 papers meeting the inclusion criteria; no papers reported on the outcomes of PMPs delivered in the UK. Of the papers obtained, four reported on PMPs conducted outside the UK; eight reported on ethnic differences in patients seeking support from pain management services in America; and the remaining papers included literature reviews, an experimental pain study, a collaborative enquiry, and a survey of patient and clinician ratings of pain. The findings indicate a lack of research into UK-based pain management for ethnic minorities and non-English-speaking patients. The literature suggests that effective PMPs must be tailored to meet cultural experiences of pain and beliefs about pain management. There is a need for further research to explore these cultural beliefs in non-English-speaking groups in the UK. Culturally sensitive evaluations of interpreted PMPs with long-term follow-up are needed to assess the effectiveness of current provision. Copyright © 2015 John Wiley & Sons, Ltd.
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Phospholipid oxidation can generate reactive and electrophilic products that are capable of modifying proteins, especially at cysteine, lysine and histidine residues. Such lipoxidation reactions are known to alter protein structure and function, both with gain of function and loss of activity effects. As well as potential importance in the redox regulation of cell behaviour, lipoxidation products in plasma could also be useful biomarkers for stress conditions. Although studies with antibodies suggested the occurrence of lipoxidation adducts on ApoB-100, these products had not previously been characterized at a molecular level. We have developed new mass spectrometry-based approaches to detect and locate adducts of oxidized phospholipids in plasma proteins, as well as direct oxidation modifications of proteins, which avoid some of the problems typically encountered with database search engines leading to erroneous identifications of oxidative PTMs. This approach uses accurate mass extracted ion chromatograms (XICs) of fragment ions from peptides containing oxPTMs, and allows multiple modifications to be examined regardless of the protein that contains them. For example, a reporter ion at 184.074 Da/e corresponding to phosphocholine indicated the presence of oxidized phosphatidylcholine adducts, while 2 reporter ions at 100.078 and 82.025 Da/e were selective for allysine. ApoB-100-oxidized phospholipid adducts were detected even in healthy human samples, as well as LDL from patients with inflammatory disease. Lipidomic studies showed that more than 350 different species of lipid were present in LDL, and were altered in disease conditions. LDL clearly represents a very complex carrier system and one that offers a rich source of information about systemic conditions, with potential as indicators of oxidative damage in ageing or inflammatory diseases.
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This study is to theoretically investigate shockwave and microbubble formation due to laser absorption by microparticles and nanoparticles. The initial motivation for this research was to understand the underlying physical mechanisms responsible for laser damage to the retina, as well as the predict threshold levels for damage for laser pulses with of progressively shorter durations. The strongest absorbers in the retina are micron size melanosomes, and their absorption of laser light causes them to accrue very high energy density. I theoretically investigate how this absorbed energy is transferred to the surrounding medium. For a wide range of conditions I calculate shockwave generation and bubble growth as a function of the three parameters; fluence, pulse duration and pulse shape. In order to develop a rigorous physical treatment, the governing equations for the behavior of an absorber and for the surrounding medium are derived. Shockwave theory is investigated and the conclusion is that a shock pressure explanation is likely to be the underlying physical cause of retinal damage at threshold fluences for sub-nanosecond pulses. The same effects are also expected for non-biological micro and nano absorbers. ^
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Seagrass is expected to benefit from increased carbon availability under future ocean acidification. This hypothesis has been little tested by in situ manipulation. To test for ocean acidification effects on seagrass meadows under controlled CO2/pH conditions, we used a Free Ocean Carbon Dioxide Enrichment (FOCE) system which allows for the manipulation of pH as continuous offset from ambient. It was deployed in a Posidonia oceanica meadow at 11 m depth in the Northwestern Mediterranean Sea. It consisted of two benthic enclosures, an experimental and a control unit both 1.7 m**3, and an additional reference plot in the ambient environment (2 m**2) to account for structural artifacts. The meadow was monitored from April to November 2014. The pH of the experimental enclosure was lowered by 0.26 pH units for the second half of the 8-month study. The greatest magnitude of change in P. oceanica leaf biometrics, photosynthesis, and leaf growth accompanied seasonal changes recorded in the environment and values were similar between the two enclosures. Leaf thickness may change in response to lower pH but this requires further testing. Results are congruent with other short-term and natural studies that have investigated the response of P. oceanica over a wide range of pH. They suggest any benefit from ocean acidification, over the next century (at a pH of 7.7 on the total scale), on Posidonia physiology and growth may be minimal and difficult to detect without increased replication or longer experimental duration. The limited stimulation, which did not surpass any enclosure or seasonal effect, casts doubts on speculations that elevated CO2 would confer resistance to thermal stress and increase the buffering capacity of meadows.
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Acknowledgements We thank Philippe Bolifraud (INRA, France), Krawiec Angele, Sandra Grange, Laurence Puillet-Anselme (CHU Grenoble, France) and Margaret Fraser (Aberdeen, UK) for their expert technical assistance. The authors also thank the staff of the sheep sheds of Jouy-en-Josas (INRA, France). The authors would also like to thank the anonymous reviewers for their close examination of this article and their useful comments.
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Thermodynamic stability measurements on proteins and protein-ligand complexes can offer insights not only into the fundamental properties of protein folding reactions and protein functions, but also into the development of protein-directed therapeutic agents to combat disease. Conventional calorimetric or spectroscopic approaches for measuring protein stability typically require large amounts of purified protein. This requirement has precluded their use in proteomic applications. Stability of Proteins from Rates of Oxidation (SPROX) is a recently developed mass spectrometry-based approach for proteome-wide thermodynamic stability analysis. Since the proteomic coverage of SPROX is fundamentally limited by the detection of methionine-containing peptides, the use of tryptophan-containing peptides was investigated in this dissertation. A new SPROX-like protocol was developed that measured protein folding free energies using the denaturant dependence of the rate at which globally protected tryptophan and methionine residues are modified with dimethyl (2-hydroxyl-5-nitrobenzyl) sulfonium bromide and hydrogen peroxide, respectively. This so-called Hybrid protocol was applied to proteins in yeast and MCF-7 cell lysates and achieved a ~50% increase in proteomic coverage compared to probing only methionine-containing peptides. Subsequently, the Hybrid protocol was successfully utilized to identify and quantify both known and novel protein-ligand interactions in cell lysates. The ligands under study included the well-known Hsp90 inhibitor geldanamycin and the less well-understood omeprazole sulfide that inhibits liver-stage malaria. In addition to protein-small molecule interactions, protein-protein interactions involving Puf6 were investigated using the SPROX technique in comparative thermodynamic analyses performed on wild-type and Puf6-deletion yeast strains. A total of 39 proteins were detected as Puf6 targets and 36 of these targets were previously unknown to interact with Puf6. Finally, to facilitate the SPROX/Hybrid data analysis process and minimize human errors, a Bayesian algorithm was developed for transition midpoint assignment. In summary, the work in this dissertation expanded the scope of SPROX and evaluated the use of SPROX/Hybrid protocols for characterizing protein-ligand interactions in complex biological mixtures.
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The overall purpose of this study was to explain the overlap and distinctiveness of non-suicidal self-injury (NSSI) and suicidality from a diathesis-stress perspective. The first part of this study evaluated the third variable theory as an explanation for the high rates of lifetime co-occurrence between NSSI and suicidality. Specifically, it was hypothesized that these forms of self-harm share a common vulnerability profile comprised of five affective, cognitive and behavioural diatheses. The second part of this study tested the hypothesis that NSSI and suicidality become distinguishable on the basis of immediate, proximal stressors, namely psychache and survival and coping beliefs (SCB). Participants (N = 262) were community individuals aged 16-24 years who reported either no history of self-harm (i.e., no history of NSSI, suicidality, or both), a history of NSSI, suicidality or both, or current NSSI-only or current NSSI+suicidality. They were recruited online to complete an online battery of questionnaires. Using a set of discriminant function analyses, it was found that the vulnerability profile was unable to distinguish between the three self-harm groups, but was able to differentiate the no self-harm group from a collated self-harm group. Result patterns were also analyzed for gender differences. It was also found that a current NSSI+suicidality group exhibited significantly higher psychache and lower SCB (for women only) than a current NSSI-only group. These results suggest that NSSI and suicidality may tend to co-occur because they have similar long-term diatheses, but that they may become more distinct with respect to immediate psychological stressors.
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This study investigates topology optimization of energy absorbing structures in which material damage is accounted for in the optimization process. The optimization objective is to design the lightest structures that are able to absorb the required mechanical energy. A structural continuity constraint check is introduced that is able to detect when no feasible load path remains in the finite element model, usually as a result of large scale fracture. This assures that designs do not fail when loaded under the conditions prescribed in the design requirements. This continuity constraint check is automated and requires no intervention from the analyst once the optimization process is initiated. Consequently, the optimization algorithm proceeds towards evolving an energy absorbing structure with the minimum structural mass that is not susceptible to global structural failure. A method is also introduced to determine when the optimization process should halt. The method identifies when the optimization method has plateaued and is no longer likely to provide improved designs if continued for further iterations. This provides the designer with a rational method to determine the necessary time to run the optimization and avoid wasting computational resources on unnecessary iterations. A case study is presented to demonstrate the use of this method.
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Background
It is generally acknowledged that a functional understanding of a biological system can only be obtained by an understanding of the collective of molecular interactions in form of biological networks. Protein networks are one particular network type of special importance, because proteins form the functional base units of every biological cell. On a mesoscopic level of protein networks, modules are of significant importance because these building blocks may be the next elementary functional level above individual proteins allowing to gain insight into fundamental organizational principles of biological cells.
Results
In this paper, we provide a comparative analysis of five popular and four novel module detection algorithms. We study these module prediction methods for simulated benchmark networks as well as 10 biological protein interaction networks (PINs). A particular focus of our analysis is placed on the biological meaning of the predicted modules by utilizing the Gene Ontology (GO) database as gold standard for the definition of biological processes. Furthermore, we investigate the robustness of the results by perturbing the PINs simulating in this way our incomplete knowledge of protein networks.
Conclusions
Overall, our study reveals that there is a large heterogeneity among the different module prediction algorithms if one zooms-in the biological level of biological processes in the form of GO terms and all methods are severely affected by a slight perturbation of the networks. However, we also find pathways that are enriched in multiple modules, which could provide important information about the hierarchical organization of the system
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Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily Living (ADL) such as eating, cooking, etc. In general, the sensors employed (e.g. PIR sensors, contact sensors) provide low resolution information. Meanwhile, the expansion of ubiquitous computing allows researchers to gather additional information from different types of sensor which is possible to improve activity analysis. Based on the previous research about sitting posture detection, this research attempts to further analyses human sitting activity. The aim of this research is to use non-intrusive low cost pressure sensor embedded chair system to recognize a subject’s activity by using their detected postures. There are three steps for this research, the first step is to find a hardware solution for low cost sitting posture detection, second step is to find a suitable strategy of sitting posture detection and the last step is to correlate the time-ordered sitting posture sequences with sitting activity. The author initiated a prototype type of sensing system called IntelliChair for sitting posture detection. Two experiments are proceeded in order to determine the hardware architecture of IntelliChair system. The prototype looks at the sensor selection and integration of various sensor and indicates the best for a low cost, non-intrusive system. Subsequently, this research implements signal process theory to explore the frequency feature of sitting posture, for the purpose of determining a suitable sampling rate for IntelliChair system. For second and third step, ten subjects are recruited for the sitting posture data and sitting activity data collection. The former dataset is collected byasking subjects to perform certain pre-defined sitting postures on IntelliChair and it is used for posture recognition experiment. The latter dataset is collected by asking the subjects to perform their normal sitting activity routine on IntelliChair for four hours, and the dataset is used for activity modelling and recognition experiment. For the posture recognition experiment, two Support Vector Machine (SVM) based classifiers are trained (one for spine postures and the other one for leg postures), and their performance evaluated. Hidden Markov Model is utilized for sitting activity modelling and recognition in order to establish the selected sitting activities from sitting posture sequences.2. After experimenting with possible sensors, Force Sensing Resistor (FSR) is selected as the pressure sensing unit for IntelliChair. Eight FSRs are mounted on the seat and back of a chair to gather haptic (i.e., touch-based) posture information. Furthermore, the research explores the possibility of using alternative non-intrusive sensing technology (i.e. vision based Kinect Sensor from Microsoft) and find out the Kinect sensor is not reliable for sitting posture detection due to the joint drifting problem. A suitable sampling rate for IntelliChair is determined according to the experiment result which is 6 Hz. The posture classification performance shows that the SVM based classifier is robust to “familiar” subject data (accuracy is 99.8% with spine postures and 99.9% with leg postures). When dealing with “unfamiliar” subject data, the accuracy is 80.7% for spine posture classification and 42.3% for leg posture classification. The result of activity recognition achieves 41.27% accuracy among four selected activities (i.e. relax, play game, working with PC and watching video). The result of this thesis shows that different individual body characteristics and sitting habits influence both sitting posture and sitting activity recognition. In this case, it suggests that IntelliChair is suitable for individual usage but a training stage is required.