Targeting the glycoprotein 130 receptor subunit to control pain and inflammation

The glycoprotein 130 (gp130) is a shared signal-transducing-membrane-associated receptor for several hematopoietic cytokines. Its activation is implicated in pain and in a variety of diseases via signaling of proinflammatory cytokines. These include interleukin-6 (IL-6) subfamily cytokines, many of which play important roles in the pathogenesis of diseases such as rheumatoid arthritis, Castleman's disease, and Kaposi's sarcoma. Several strategies have been developed to block gp130-receptor-mediated signaling. These include the application of monoclonal antibodies, the creation of mutant form(s) of the gp130 with increased binding affinity for such ligands as IL-6/sIL-6R complex, and the generation of antagonists by selective mutagenesis of the specific cytokine/gp130 receptor binding site(s). Other strategies include targeting gp130-mediated signaling pathways such as that involving signal transducer and activator of transcription-3. This review provides a summary of the latest research pertaining to the role of gp130 in the pathogenesis of inflammatory and other diseases in which the gp130 receptor is implicated. An overview of antagonists targeting the gp130 receptor is included with particular emphasis on their mechanism of action and their limitations and potential for therapeutic application.

Density and cross-sectional areas of axons in the olfactory tract in control subjects and Alzheimer's disease:an image analysis study

Objective. Using an image analysis system to determine whether there is loss of axons in the olfactory tract (OT) in Alzheimer’s disease (AD). Design. A retrospective neuropathological study. Patients Nine control patients and eight clinically and pathologically verified AD cases. Measurements and Results. There was a reduction in axon density in AD compared with control subjects in the central and peripheral regions of the tract. Axonal loss was mainly of axons with smaller (<2.99 µm2) myelinated cross-sectional areas. Conclusions. The data suggest significant degeneration of axons within the OT involving the smaller sized axons. Loss of axons in the OT is likely to be secondary to pathological changes originating within the parahippocampal gyrus rather than to a pathogen spreading into the brain via the olfactory pathways.

Recombinant protein production in yeast:methods and protocols

In the last few years, significant advances have been made in understanding how a yeast cell responds to the stress of producing a recombinant protein, and how this information can be used to engineer improved host strains. The molecular biology of the expression vector, through the choice of promoter, tag and codon optimization of the target gene, is also a key determinant of a high-yielding protein production experiment. Recombinant Protein Production in Yeast: Methods and Protocols examines the process of preparation of expression vectors, transformation to generate high-yielding clones, optimization of experimental conditions to maximize yields, scale-up to bioreactor formats and disruption of yeast cells to enable the isolation of the recombinant protein prior to purification. Written in the highly successful Methods in Molecular Biology™ series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.

Analysis of variables measured in the visual screening of University of Birmingham freshmen and a critical review of visual screening methods and approach

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Knowledge workers and their relationships with organisations

The programme of research examines knowledge workers, their relationships with organisations, and perceptions of management practices through the development of a theoretical model and knowledge worker archetypes. Knowledge worker and non-knowledge worker archetypes were established through an analysis of the extant literature. After an exploratory study of knowledge workers in a small software development company the archetypes were refined to include occupational classification data and the findings from Study 1. The Knowledge Worker Characteristics Model (KWCM) was developed as a theoretical framework in order to analyse differences between the two archetypes within the IT sector. The KWCM comprises of the variables within the job characteristics model, creativity, goal orientation, identification and commitment. In Study 2, a global web based survey was conducted. There were insufficient non-knowledge worker responses and therefore a cluster analysis was conducted to interrogate the archetypes further. This demonstrated, unexpectedly, that that there were marked differences within the knowledge worker archetypes suggesting the need to granulate the archetype further. The theoretical framework and the archetypes were revised (as programmers and web developers) and the research study was refocused to examine occupational differences within knowledge work. Findings from Study 2 identified that there were significant differences between the archetypes in relation to the KWCM. 19 semi-structured interviews were conducted in Study 3 in order to deepen the analysis using qualitative data and to examine perceptions of people management practices. The findings from both studies demonstrate that there were significant differences between the two groups but also that job challenge, problem solving, intrinsic reward and team identification were of importance to both groups of knowledge workers. This thesis presents an examination of knowledge workers’ perceptions of work, organisations and people management practices in the granulation and differentiation of occupational archetypes.

Student response to a pub quiz style first year psychology assessment

The deterioration in staff-student ratios in UK higher education has had a disproportionate impact on assessment and feedback, meaning that contemporary students may have fewer assessments and much less feedback than a generation ago (Gibbs, 2006). Early use of a quiz assessment may offer a blend of social benefits (social comparison, shared problem solving leading to engagement, belonging and continuation), academic benefits (early formative assessment, immediate feedback) and administrative benefits (on-the-spot verbal marking and feedback to 230 students simultaneously). This study sought student views on the acceptability and contribution to learning of the quiz. Social benefits were apparent but difficulties in creating questions to elicit deeper reasoning and problem solving are discussed and the quiz had limited pedagogic value in the eyes of participants. The use of assertion-reason questions are considered as a way of taking the table quiz to a higher level and extending its pedagogic value.

A mixture density network approach to modelling and exploiting uncertainty in nonlinear control problems

In nonlinear and stochastic control problems, learning an efficient feed-forward controller is not amenable to conventional neurocontrol methods. For these approaches, estimating and then incorporating uncertainty in the controller and feed-forward models can produce more robust control results. Here, we introduce a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. A nonlinear multi-variable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non-Gaussian distributions of control signal as well as processes with hysteresis. © 2004 Elsevier Ltd. All rights reserved.

Exploiting uncertainty in nonlinear stochastic control problem

This work introduces a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. Convergence of the output error for the proposed control method is verified by using a Lyapunov function. Several simulation examples are provided to demonstrate the efficiency of the developed control method. The manner in which such a method is extended to nonlinear multi-variable systems with different delays between the input-output pairs is considered and demonstrated through simulation examples.