Drug-protein interaction studied by technique of microdialysis combined with high performance liquid chromatography

Drug-protein binding is an important process in determining the activity and fate of a pharmaceutical agent once it has entered the body. This review examines the method of microdialysis combined with high-performance liquid chromatography (HPLC) that has been developed;by ours to study such interactions, in which the microdialysis was applied to sample the free drug in the mixed solution of drug with protein, and HPLC to quantify the concentration of free drug in the microdialysate. This technique has successfully been used for determining various types of binding interactions between the low affinity drugs, high affinity drugs and enantiomers to HSA. For the case of competitive binding of two drugs to a protein in solution, a displacement equation has been derived and examined with four nonsteroidal anti-inflammatory drugs and HSA as model drugs and protein, respectively. Microdialysis with HPLC was adopted to determine simultaneously the free solute and displacing agent in drug-protein solutions. The method is able to locate the binding site and determine affinity constants even up to 10(7) L/mol accurately.

工作幸福感的结构、测量及作用机制

With the emergence and development of positive psychology, happiness has been the focus of academia and business. However, there is no uniform measure of happiness, because of many different theories of happiness, which are not compatible with others. It bounds the further development of happiness theory. It is also the same with the research of work well-being, which refers to the emotional experience and quality of psychological functioning of employee in the workplace. Subjective well-being (SWB) and psychological well-being (PWB) are two major theories of happiness. Prior research has demonstrated the integration of these two theories theoretically, but still needs more empirical support. Besides, in line with the development of positive psychology, a body of knowledge about positive leadership is advocated. Transformational leadership is treated as one kind of positive leadership, since it emphasizes the leader’s motivational and elevating effect on followers. But the extent to which the transformational leadership can enhance work well-being, and what the mechanism is, these are the questions need to be explored. Based on the integration of SWB and PWB, this research tried to investigate the structure, measurement and mechanism of work well-being, and combining with the theory of transformational leadership, this study also tried to investigate the relationship between transformational leadership and work well-being. The structure and measurement of work well-being, the relationships between work well-being and job characteristics (including job resources and job demands), the relationships among transformational leadership, job resources, work well-being and corresponding outcomes, the relationships among transformational leadership, job demands, work well-being and corresponding outcomes, and the relationships among transformational leadership, group job characteristics, group work well-being and corresponding group outcomes were explored by using content analysis, Subject Matter Experts (SMEs) discussion, and structural questionnaire surveys. More than 7000 subjects were surveyed, and Explore Factor Analysis (EFA), Confirm Factor Analysis (CFA), Structural Equation Modeling (SEM), Hierarchical Linear Modeling (HLM) and other statistics methods were used. The following is the major conclusions. Firstly, work well-being is a two high-order factors structure, which includes affective well-being (AWB) and cognitive well-being (CWB). AWB is similar to SWB, and CWB is similar to PWB. Besides, the construct of AWB includes sub-dimensions of positive emotional experience and negative emotional experience. And the construct of CWB consists of work autonomy, personal growth, work competent, and work significance. Secondly, the relationships between job characteristics and AWB and CWB are different. On one hand job demands are directly related to AWB, and are indirectly related to CWB through the full mediation of AWB, on the other job resources are directly related to CWB, and are indirectly related to AWB through the full mediation of CWB, which means AWB and CWB reciprocally influences each other in the model of job demands-resources. These results were concluded as the process model of work well-being. Thirdly, AWB and CWB are positively related to many workplace outcomes, including job satisfaction, group satisfaction, organizational commitment, turnover intention, job performance, organizational citizenship behavior (OCB), and general psychological health and general physiological health. Fourthly, transformational leadership is indirectly related to CWB through the full mediation of job resources, and is related to AWB through the partial mediation of job demands. Meanwhile, transformational leadership is related to many workplace outcomes through the mediation of job characteristics and work well-being. These results implied that transformational leadership is indeed one kind of positive leadership. Fifthly, in the group level, transformational leadership is indirectly related to group CWB through the full mediation of group job resources, and is related to group AWB through the full mediation of group job demands. Group AWB has positive influence on group CWB, but not vice versa. Group job characteristics and group work well-being fully mediate the relationships between transformational leadership and intragroup cooperation and group performance.

The Image Irradiance Equation: Its Solution and Application

How much information about the shape of an object can be inferred from its image? In particular, can the shape of an object be reconstructed by measuring the light it reflects from points on its surface? These questions were raised by Horn [HO70] who formulated a set of conditions such that the image formation can be described in terms of a first order partial differential equation, the image irradiance equation. In general, an image irradiance equation has infinitely many solutions. Thus constraints necessary to find a unique solution need to be identified. First we study the continuous image irradiance equation. It is demonstrated when and how the knowledge of the position of edges on a surface can be used to reconstruct the surface. Furthermore we show how much about the shape of a surface can be deduced from so called singular points. At these points the surface orientation is uniquely determined by the measured brightness. Then we investigate images in which certain types of silhouettes, which we call b-silhouettes, can be detected. In particular we answer the following question in the affirmative: Is there a set of constraints which assure that if an image irradiance equation has a solution, it is unique? To this end we postulate three constraints upon the image irradiance equation and prove that they are sufficient to uniquely reconstruct the surface from its image. Furthermore it is shown that any two of these constraints are insufficient to assure a unique solution to an image irradiance equation. Examples are given which illustrate the different issues. Finally, an overview of known numerical methods for computing solutions to an image irradiance equation are presented.

Reading the rhetoric of nationhood in two Reformation pamphlets by Richard Morison and Nicholas Bodrugan

Mottram, S. (2005). Reading the rhetoric of nationhood in two Reformation pamphlets by Richard Morison and Nicholas Bodrugan. Renaissance Studies. 19(4), pp.523-540. RAE2008

Clergy, crusified within the body of Christ - a challenge to pastoral care

M.A. Thesis / University of Pretoria / Department of Practical Theology / Advised by Prof M Masango

Inferring Body Pose without Tracking Body Parts

A novel approach for estimating articulated body posture and motion from monocular video sequences is proposed. Human pose is defined as the instantaneous two dimensional configuration (i.e., the projection onto the image plane) of a single articulated body in terms of the position of a predetermined set of joints. First, statistical segmentation of the human bodies from the background is performed and low-level visual features are found given the segmented body shape. The goal is to be able to map these, generally low level, visual features to body configurations. The system estimates different mappings, each one with a specific cluster in the visual feature space. Given a set of body motion sequences for training, unsupervised clustering is obtained via the Expectation Maximation algorithm. Then, for each of the clusters, a function is estimated to build the mapping between low-level features to 3D pose. Currently this mapping is modeled by a neural network. Given new visual features, a mapping from each cluster is performed to yield a set of possible poses. From this set, the system selects the most likely pose given the learned probability distribution and the visual feature similarity between hypothesis and input. Performance of the proposed approach is characterized using a new set of known body postures, showing promising results.

Estimating Human Body Pose from a Single Image via the Specialized Mappings Architecture

A non-linear supervised learning architecture, the Specialized Mapping Architecture (SMA) and its application to articulated body pose reconstruction from single monocular images is described. The architecture is formed by a number of specialized mapping functions, each of them with the purpose of mapping certain portions (connected or not) of the input space, and a feedback matching process. A probabilistic model for the architecture is described along with a mechanism for learning its parameters. The learning problem is approached using a maximum likelihood estimation framework; we present Expectation Maximization (EM) algorithms for two different instances of the likelihood probability. Performance is characterized by estimating human body postures from low level visual features, showing promising results.

Neural Representations for Sensory-Motor Control, III: Learning a Body-Centered Representation of 3-D Target Position

A neural model is described of how the brain may autonomously learn a body-centered representation of 3-D target position by combining information about retinal target position, eye position, and head position in real time. Such a body-centered spatial representation enables accurate movement commands to the limbs to be generated despite changes in the spatial relationships between the eyes, head, body, and limbs through time. The model learns a vector representation--otherwise known as a parcellated distributed representation--of target vergence with respect to the two eyes, and of the horizontal and vertical spherical angles of the target with respect to a cyclopean egocenter. Such a vergence-spherical representation has been reported in the caudal midbrain and medulla of the frog, as well as in psychophysical movement studies in humans. A head-centered vergence-spherical representation of foveated target position can be generated by two stages of opponent processing that combine corollary discharges of outflow movement signals to the two eyes. Sums and differences of opponent signals define angular and vergence coordinates, respectively. The head-centered representation interacts with a binocular visual representation of non-foveated target position to learn a visuomotor representation of both foveated and non-foveated target position that is capable of commanding yoked eye movementes. This head-centered vector representation also interacts with representations of neck movement commands to learn a body-centered estimate of target position that is capable of commanding coordinated arm movements. Learning occurs during head movements made while gaze remains fixed on a foveated target. An initial estimate is stored and a VOR-mediated gating signal prevents the stored estimate from being reset during a gaze-maintaining head movement. As the head moves, new estimates arc compared with the stored estimate to compute difference vectors which act as error signals that drive the learning process, as well as control the on-line merging of multimodal information.

Nutrition, growth and body composition in infancy

This thesis is presented in two parts. Data for this research is from the Cork BASELINE (Babies after SCOPE, Evaluating Longitudinal Impact using Neurological and Nutritional Endpoints) Birth Cohort Study (n = 2137). In this prospective birth cohort study, pediatric follow-up with in-person appointments were repeated from the time of birth through to 2, 6 and 12 months, and at 2 years. Body composition was measured by air displacement plethysmography at birth and at 2 months using the PEA POD Infant Body Composition Tracking System. This thesis provides the first extensive report on the study’s 2 year assessment. In part one, the aims were to investigate potential early-life risk factors for childhood overweight and obesity, including rapid growth and body composition in infancy and umbilical cord concentrations of leptin and high molecular weight (HMW) adiponectin. This research is the first to describe rapid growth in early infancy in terms of changes in direct measures of body composition. These are also the first data to examine associations between umbilical cord leptin and HMW adiponectin concentrations and changes in fat and lean mass in early infancy. These data provide additional insight into characterising the growth trajectory in infancy and into the role of perinatal factors in determining infant growth and subsequent overweight/obesity risk. In part two of this thesis, the aims were to quantify vitamin D intake and status at 2 years and to investigate whether 25-hydroxyvitamin D [25(OH)D] concentrations in early pregnancy and in umbilical cord blood are associated with infant growth and body composition. There was a low prevalence of vitamin D deficiency among Irish 2 year olds (n = 742) despite a high prevalence of inadequate intakes and high latitude (51°N). Maternal 25(OH)D concentrations at 15 weeks gestation and cord 25(OH)D concentrations at delivery were not associated with infant growth or adiposity.

Scaling limits of a model for selection at two scales

The dynamics of a population undergoing selection is a central topic in evolutionary biology. This question is particularly intriguing in the case where selective forces act in opposing directions at two population scales. For example, a fast-replicating virus strain outcompetes slower-replicating strains at the within-host scale. However, if the fast-replicating strain causes host morbidity and is less frequently transmitted, it can be outcompeted by slower-replicating strains at the between-host scale. Here we consider a stochastic ball-and-urn process which models this type of phenomenon. We prove the weak convergence of this process under two natural scalings. The first scaling leads to a deterministic nonlinear integro-partial differential equation on the interval $[0,1]$ with dependence on a single parameter, $\lambda$. We show that the fixed points of this differential equation are Beta distributions and that their stability depends on $\lambda$ and the behavior of the initial data around $1$. The second scaling leads to a measure-valued Fleming-Viot process, an infinite dimensional stochastic process that is frequently associated with a population genetics.

Improving Indwelling Glucose Sensor Performance: Porous, Dexamethasone-Releasing Coatings that Modulate the Foreign Body Response

Inflammation and the formation of an avascular fibrous capsule have been identified as the key factors controlling the wound healing associated failure of implantable glucose sensors. Our aim is to guide advantageous tissue remodeling around implanted sensor leads by the temporal release of dexamethasone (Dex), a potent anti-inflammatory agent, in combination with the presentation of a stable textured surface.

First, Dex-releasing polyurethane porous coatings of controlled pore size and thickness were fabricated using salt-leaching/gas-foaming technique. Porosity, pore size, thickness, drug release kinetics, drug loading amount, and drug bioactivity were evaluated. In vitro sensor functionality test were performed to determine if Dex-releasing porous coatings interfered with sensor performance (increased signal attenuation and/or response times) compared to bare sensors. Drug release from coatings monitored over two weeks presented an initial fast release followed by a slower release. Total release from coatings was highly dependent on initial drug loading amount. Functional in vitro testing of glucose sensors deployed with porous coatings against glucose standards demonstrated that highly porous coatings minimally affected signal strength and response rate. Bioactivity of the released drug was determined by monitoring Dex-mediated, dose-dependent apoptosis of human peripheral blood derived monocytes in culture.

The tissue modifying effects of Dex-releasing porous coatings were accessed by fully implanting Tygon® tubing in the subcutaneous space of healthy and diabetic rats. Based on encouraging results from these studies, we deployed Dex-releasing porous coatings from the tips of functional sensors in both diabetic and healthy rats. We evaluated if the tissue modifying effects translated into accurate, maintainable and reliable sensor signals in the long-term. Sensor functionality was accessed by continuously monitoring glucose levels and performing acute glucose challenges at specified time points.

Sensors treated with porous Dex-releasing coatings showed diminished inflammation and enhanced vascularization of the tissue surrounding the implants in healthy rats. Functional sensors with Dex-releasing porous coatings showed enhanced sensor sensitivity over a 21-day period when compared to controls. Enhanced sensor sensitivity was accompanied with an increase in sensor signal lag and MARD score. These results indicated that Dex-loaded porous coatings were able to elicit a favorable tissue response, and that such tissue microenvironment could be conducive towards extending the performance window of glucose sensors in vivo.

The diabetic pilot animal study showed differences in wound healing patters between healthy and diabetic subjects. Diabetic rats showed lower levels of inflammation and vascularization of the tissue surrounding implants when compared to their healthy counterparts. Also, functional sensors treated with Dex-releasing porous coatings did not show enhanced sensor sensitivity over a 21-day period. Moreover, increased in sensor signal lag and MARD scores were present in porous coated sensors regardless of Dex-loading when compared to bare implants. These results suggest that the altered wound healing patterns presented in diabetic tissues may lead to premature sensor failure when compared to sensors implanted in healthy rats.

Accurate localized resolution of identity approach for linear-scaling hybrid density functionals and for many-body perturbation theory

© 2015 IOP Publishing Ltd and Deutsche Physikalische Gesellschaft.A key component in calculations of exchange and correlation energies is the Coulomb operator, which requires the evaluation of two-electron integrals. For localized basis sets, these four-center integrals are most efficiently evaluated with the resolution of identity (RI) technique, which expands basis-function products in an auxiliary basis. In this work we show the practical applicability of a localized RI-variant ('RI-LVL'), which expands products of basis functions only in the subset of those auxiliary basis functions which are located at the same atoms as the basis functions. We demonstrate the accuracy of RI-LVL for Hartree-Fock calculations, for the PBE0 hybrid density functional, as well as for RPA and MP2 perturbation theory. Molecular test sets used include the S22 set of weakly interacting molecules, the G3 test set, as well as the G2-1 and BH76 test sets, and heavy elements including titanium dioxide, copper and gold clusters. Our RI-LVL implementation paves the way for linear-scaling RI-based hybrid functional calculations for large systems and for all-electron many-body perturbation theory with significantly reduced computational and memory cost.

Sea Urchin Body Plan Development and Evolution: An Integrative Transcriptomic Approach

My dissertation work integrates comparative transcriptomics and functional analyses to investigate gene expression changes underlying two significant aspects of sea urchin evolution and development: the dramatic developmental changes associated with an ecologically significant shift in life history strategy and the development of the unusual radial body plan of adult sea urchins.

In Chapter 2, I investigate evolutionary changes in gene expression underlying the switch from feeding (planktotrophic) to nonfeeding (lecithotrophic) development in sea urchins. In order to identify these changes, I used Illumina RNA-seq to measure expression dynamics across 7 developmental stages in three sea urchin species: the lecithotroph Heliocidaris erythrogramma, the closely related planktotroph Heliocidaris tuberculata, and an outgroup planktotroph Lytechinus variegatus. My analyses draw on a well-characterized developmental gene regulatory network (GRN) in sea urchins to understand how the ancestral planktotrophic developmental program was altered during the evolution of lecithotrophic development. My results suggest that changes in gene expression profiles occurred more frequently across the transcriptome during the evolution of lecithotrophy than during the persistence of planktotrophy. These changes were even more pronounced within the GRN than across the transcriptome as a whole, and occurred in each network territory (skeletogenic, endomesoderm and ectoderm). I found evidence for both conservation and divergence of regulatory interactions in the network, as well as significant changes in the expression of genes with known roles in larval skeletogenesis, which is dramatically altered in lecithotrophs. I further explored network dynamics between species using coexpression analyses, which allowed me to identify novel players likely involved in sea urchin neurogenesis and endoderm patterning.

In Chapter 3, I investigate developmental changes in gene expression underlying radial body plan development and metamorphosis in H. erythrogramma. Using Illumina RNA-seq, I measured gene expression profiles across larval, metamorphic, and post-metamorphic life cycle phases. My results present a high-resolution view of gene expression dynamics during the complex transition from pre- to post-metamorphic development and suggest that distinct sets of regulatory and effector proteins are used during different life history phases.

Collectively, my investigations provide an important foundation for future, empirical studies to investigate the functional role of gene expression change in the evolution of developmental differences between species and also for the generation of the unusual radial body plan of sea urchins.

Consistent couplings between fields with a gauge freedom and deformations of the master equation

The antibracket in the antifield-BRST formalism is known to define a map Hp × Hq → Hp + q + 1 associating with two equivalence classes of BRST invariant observables of respective ghost number p and q an equivalence class of BRST invariant observables of ghost number p + q + 1. It is shown that this map is trivial in the space of all functionals, i.e. that its image contains only the zeroth class. However, it is generically non-trivial in the space of local functionals. Implications of this result for the problem of consistent interactions among fields with a gauge freedom are then drawn. It is shown that the obstructions to constructing non-trivial such interactions lie precisely in the image of the antibracket map and are accordingly non-existent if one does not insist on locality. However consistent local interactions are severely constrained. The example of the Chern-Simons theory is considered. It is proved that the only consistent, local, Lorentz covariant interactions for the abelian models are exhausted by the non-abelian Chern-Simons extensions. © 1993.

A multi-scale atomistic-continuum modelling of crack propagation in a two-dimensional macroscopic plate

A novel multi-scale seamless model of brittle-crack propagation is proposed and applied to the simulation of fracture growth in a two-dimensional Ag plate with macroscopic dimensions. The model represents the crack propagation at the macroscopic scale as the drift-diffusion motion of the crack tip alone. The diffusive motion is associated with the crack-tip coordinates in the position space, and reflects the oscillations observed in the crack velocity following its critical value. The model couples the crack dynamics at the macroscales and nanoscales via an intermediate mesoscale continuum. The finite-element method is employed to make the transition from the macroscale to the nanoscale by computing the continuum-based displacements of the atoms at the boundary of an atomic lattice embedded within the plate and surrounding the tip. Molecular dynamics (MD) simulation then drives the crack tip forward, producing the tip critical velocity and its diffusion constant. These are then used in the Ito stochastic calculus to make the reverse transition from the nanoscale back to the macroscale. The MD-level modelling is based on the use of a many-body potential. The model successfully reproduces the crack-velocity oscillations, roughening transitions of the crack surfaces, as well as the macroscopic crack trajectory. The implications for a 3-D modelling are discussed.