26 resultados para Modified Direct Analysis Method


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The activation of presynaptic G protein-coupled receptors (GPCRs) is widely reported to inhibit transmitter release; however, the lack of accessibility of many presynaptic terminals has limited direct analysis of signalling mediators. We studied GPCR-mediated inhibition of fast cholinergic transmission between superior cervical ganglion neurones (SCGNs) in culture. The adrenoceptor agonist noradrenaline (NA) caused a dose-related reduction in evoked excitatory postsynaptic potentials (EPSPs). NA-induced EPSP decrease was accompanied by effects on the presynaptic action potential (AP), reducing AP duration and amplitude of the after-hyperpolarization (AHP), without affecting the pre- and postsynaptic membrane potential. All effects of NA were blocked by yohimbine and synaptic transmission was reduced by clonidine, consistent with an action at presynaptic alpha 2-adrenoceptors. NA-induced inhibition of transmission was sensitive to pre-incubation of SCGNs with pertussis toxin (PTX), implicating the involvement of G alpha(i)/(o)beta y subunits. Expression of G alpha transducin, an agent which sequesters G protein beta gamma (G beta y) subunits, in the presynaptic neurone caused a time-dependent attenuation of NA-induced inhibition. Injection of purified G beta gamma subunits into the presynaptic neurone inhibited transmission, and also reduced the AHP amplitude. Furthermore, NA-induced inhibition was occluded by pre-injection of G beta gamma subunits. The Ca2+ channel blocker Cd2+ mimicked NA effects on transmitter release. Cd2+, NA and G beta gamma subunits also inhibited somatic Ca2+ current. In contrast to effects on AP-evoked transmitter release, NA had no clear action on AP-independent EPSPs induced by hypertonic solutions. These results demonstrate that G beta gamma subunits functionally mediate inhibition of transmitter release by alpha 2-adrenoceptors and represent important regulators of synaptic transmission at mammalian presynaptic terminals.

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A new state estimator algorithm is based on a neurofuzzy network and the Kalman filter algorithm. The major contribution of the paper is recognition of a bias problem in the parameter estimation of the state-space model and the introduction of a simple, effective prefiltering method to achieve unbiased parameter estimates in the state-space model, which will then be applied for state estimation using the Kalman filtering algorithm. Fundamental to this method is a simple prefiltering procedure using a nonlinear principal component analysis method based on the neurofuzzy basis set. This prefiltering can be performed without prior system structure knowledge. Numerical examples demonstrate the effectiveness of the new approach.

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Background: The characterization of phytoestrogen intake and cancer risk has been hindered by the absence of accurate dietary phytoestrogen values. Objective: We examined the risk of breast, colorectal, and prostate cancers relative to phytoestrogen intake on the basis of a comprehensive database. Design: Demographic and anthropometric characteristics, a medical history, and 7-d records of diet were collected prospectively from participants (aged 40–79 y) in the European Prospective Investigation into Cancer and Nutrition–Norfolk (EPIC-Norfolk). Five hundred nine food items were analyzed by liquid chromatography–mass spectrometry/mass spectrometry, and 13C3-labeled internal standards were analyzed for isoflavones (genistein, daidzein, glycitein, biochanin A, and formononetin), lignans (secoisolariciresinol and matairesinol), and enterolignans from gut microbial metabolism in animal food sources (equol and enterolactone). From the direct analysis, values for 10,708 foods were calculated. Odds ratios (ORs) for breast (244 cases, 941 controls), colorectal (221 cases, 886 controls), and prostate (204 cases, 812 controls) cancers were calculated relative to phytoestrogen intake. Results: Phytoestrogen intake was not associated with breast cancer among women or colorectal cancer among men. Among women, colorectal cancer risk was inversely associated with enterolactone (OR: 0.33; 95% CI: 0.14, 0.74) and total enterolignans (OR: 0.32; 95% CI: 0.13, 0.79), with a positive trend detected for secoisolariciresinol (OR: 1.60; 95% CI: 0.96, 2.69). A positive trend between enterolignan intake and prostate cancer risk (OR: 1.27; 95% CI: 0.97, 1.66) was attenuated after adjustment for dairy intake (OR: 1.19; 95% CI: 0.77, 1.82). Conclusion: Dietary phytoestrogens may contribute to the risk of colorectal cancer among women and prostate cancer among men.

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Working memory (WM) is not a unitary construct. There are distinct processes involved in encoding information, maintaining it on-line, and using it to guide responses. The anatomical configurations of these processes are more accurately analyzed as functionally connected networks than collections of individual regions. In the current study we analyzed event-related functional magnetic resonance imaging (fMRI) data from a Sternberg Item Recognition Paradigm WM task using a multivariate analysis method that allowed the linking of functional networks to temporally-separated WM epochs. The length of the delay epochs was varied to optimize isolation of the hemodynamic response (HDR) for each task epoch. All extracted functional networks displayed statistically significant sensitivity to delay length. Novel information extracted from these networks that was not apparent in the univariate analysis of these data included involvement of the hippocampus in encoding/probe, and decreases in BOLD signal in the superior temporal gyrus (STG), along with default-mode regions, during encoding/delay. The bilateral hippocampal activity during encoding/delay fits with theoretical models of WM in which memoranda held across the short term are activated long-term memory representations. The BOLD signal decreases in the STG were unexpected, and may reflect repetition suppression effects invoked by internal repetition of letter stimuli. Thus, analysis methods focusing on how network dynamics relate to experimental conditions allowed extraction of novel information not apparent in univariate analyses, and are particularly recommended for WM experiments for which task epochs cannot be randomized.

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Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

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A generalized asymptotic expansion in the far field for the problem of cylindrical wave reflection at a homogeneous impedance plane is derived. The expansion is shown to be uniformly valid over all angles of incidence and values of surface impedance, including the limiting cases of zero and infinite impedance. The technique used is a rigorous application of the modified steepest descent method of Ot

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Sub-seasonal variability including equatorial waves significantly influence the dehydration and transport processes in the tropical tropopause layer (TTL). This study investigates the wave activity in the TTL in 7 reanalysis data sets (RAs; NCEP1, NCEP2, ERA40, ERA-Interim, JRA25, MERRA, and CFSR) and 4 chemistry climate models (CCMs; CCSRNIES, CMAM, MRI, and WACCM) using the zonal wave number-frequency spectral analysis method with equatorially symmetric-antisymmetric decomposition. Analyses are made for temperature and horizontal winds at 100 hPa in the RAs and CCMs and for outgoing longwave radiation (OLR), which is a proxy for convective activity that generates tropopause-level disturbances, in satellite data and the CCMs. Particular focus is placed on equatorial Kelvin waves, mixed Rossby-gravity (MRG) waves, and the Madden-Julian Oscillation (MJO). The wave activity is defined as the variance, i.e., the power spectral density integrated in a particular zonal wave number-frequency region. It is found that the TTL wave activities show significant difference among the RAs, ranging from ∼0.7 (for NCEP1 and NCEP2) to ∼1.4 (for ERA-Interim, MERRA, and CFSR) with respect to the averages from the RAs. The TTL activities in the CCMs lie generally within the range of those in the RAs, with a few exceptions. However, the spectral features in OLR for all the CCMs are very different from those in the observations, and the OLR wave activities are too low for CCSRNIES, CMAM, and MRI. It is concluded that the broad range of wave activity found in the different RAs decreases our confidence in their validity and in particular their value for validation of CCM performance in the TTL, thereby limiting our quantitative understanding of the dehydration and transport processes in the TTL.

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Therapeutic activation of Toll-like receptors (TLR) has potential for cancer immunotherapy, for augmenting the activity of anti-tumor monoclonal antibodies (mAbs), and for improved vaccine adjuvants. A previous attempt to specifically target TLR agonists to dendritic cells (DC) using mAbs failed because conjugation led to non-specific binding and mAbs lost specificity. We demonstrate here for the first time the successful conjugation of a small molecule TLR7 agonist to an anti-tumour mAb (the anti-hCD 20 rituximab) without compromising antigen specificity. The TLR7 agonist UC-1V150 was conjugated to rituximab using two conjugation methods and yield, molecular substitution ratio, retention of TLR7 activity and specificity of antigen binding were compared. Both conjugation methods produced rituximab-UC-1V150 conjugates with UC-1V150 : rituximab ratio ranging from 1:1 to 3:1 with drug loading quantified by UV spectroscopy and drug substitution ratio verified by MALDI TOF mass spectroscopy. The yield of purified conjugates varied with conjugation method, and dropped as low as 31% using a method previously described for conjugating UC-1V150 to proteins, where a bifunctional crosslinker was firstly reacted with rituximab, and secondly to the TLR7 agonist. We therefore developed a direct conjugation method by producing an amine-reactive UV active version of UC-1V150, termed NHS:UC-1V150. Direct conjugation with NHS:UC-1V150 was quick and simple and gave improved conjugate yields of 65-78%. Rituximab-UC-1V150 conjugates had the expected pro-inflammatory activity in vitro (EC50 28-53 nM) with a significantly increased activity over unconjugated UC-1V150 (EC50 547 nM). Antigen binding and specificity of the rituxuimab-UC-1V150 conjugates was retained, and after incubation with human peripheral blood leukocytes, all conjugates bound strongly only to CD20-expressing B cells whilst no non-specific binding to CD20-negative cells was observed. Selective targeting of Toll-like receptor activation directly within tumors or to DC is now feasible.

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Internal gravity waves are generated as adjustment radiation whenever a sudden change in forcing causes the atmosphere to depart from its large-scale balanced state. Such a forcing anomaly occurs during a solar eclipse, when the Moon’s shadow cools part of the Earth’s surface. The resulting atmospheric gravity waves are associated with pressure and temperature perturbations, which in principle are detectable both at the surface and aloft. In this study, surface pressure and temperature data from two UK sites at Reading and Lerwick are analysed for eclipse-driven gravity-wave perturbations during the 20 March 2015 solar eclipse over north-west Europe. Radiosonde wind data from the same two sites are also analysed using a moving parcel analysis method, to determine the periodicities of the waves aloft. On this occasion, the perturbations both at the surface and aloft are found not to be confidently attributable to eclipse-driven gravity waves. We conclude that the complex synoptic weather conditions over the UK at the time of this particular eclipse helped to mask any eclipse-driven gravity waves.

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Recent interest in the validation of general circulation models (GCMs) has been devoted to objective methods. A small number of authors have used the direct synoptic identification of phenomena together with a statistical analysis to perform the objective comparison between various datasets. This paper describes a general method for performing the synoptic identification of phenomena that can be used for an objective analysis of atmospheric, or oceanographic, datasets obtained from numerical models and remote sensing. Methods usually associated with image processing have been used to segment the scene and to identify suitable feature points to represent the phenomena of interest. This is performed for each time level. A technique from dynamic scene analysis is then used to link the feature points to form trajectories. The method is fully automatic and should be applicable to a wide range of geophysical fields. An example will be shown of results obtained from this method using data obtained from a run of the Universities Global Atmospheric Modelling Project GCM.

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The 'direct costs' attributable to 30 different endemic diseases of farm animals in Great Britain are estimated using a standardised method to construct a simple model for each disease that includes consideration of disease prevention and treatment costs. The models so far developed provide a basis for further analyses including cost-benefit analyses for the economic assessment of disease control options. The approach used reflects the inherent livestock disease information constraints, which limit the application of other economic analytical methods. It is a practical and transparent approach that is relatively easily communicated to veterinary scientists and policy makers. The next step is to develop the approach by incorporating wider economic considerations into the analyses in a way that will demonstrate to policy makers and others the importance of an economic perspective to livestock disease issues.