Is there still value in strategic group research?

This paper offers a selected review of strategic group theory and seeks to explore the benefits and limitations of modern strategic group analysis within the context of the Pharmaceutical Industry. The rise and fall of strategic group research is reviewed and some suggestions advanced as to the reasons why strategic group research has often produced conflicting results, particularly with regard to the link between group membership and performance. The review concludes that strategic group research continues to offer a valuable way to classify firms by their strategy and provides some suggestions as to how future studies may avoid the pitfalls exposed by previous research.

Doing business in India:building research-based practice

In response to the increasing interest in the growth and developments in the Indian economy, and the dynamic nature of the rapidly changing Indian business environment, this textbook is designed to provide a comprehensive guide to doing business in the Indian context. Written by academic experts in their respective fields, this book is divided into three parts: the Indian business context, conducting business in India, and India and the world. Key information is presented on a wide range of topics, including: •Both the shortcomings and opportunities associated with the Indian business environment •The economic development model in India •Critical skills for negotiation and incentives for foreign investors, including case studies of Italian companies that have entered the Indian market in different ways •Business culture in India, including particular customs and etiquette In addition to the pedagogical features, each chapter contains a set of key issues, and there is also a list of useful websites covering a wide range of business needs. This book introduces students to business in India, and will be also be of use to investors, organisations and managers who are already doing business, or intend to start one, in India.

The impact of the Val158Met catechol-O-methyltransferase genotype on neural correlates of sad facial affect processing in patients with bipolar disorder and their relatives

Background - The Met allele of the catechol-O-methyltransferase (COMT) valine-to-methionine (Val158Met) polymorphism is known to affect dopamine-dependent affective regulation within amygdala-prefrontal cortical (PFC) networks. It is also thought to increase the risk of a number of disorders characterized by affective morbidity including bipolar disorder (BD), major depressive disorder (MDD) and anxiety disorders. The disease risk conferred is small, suggesting that this polymorphism represents a modifier locus. Therefore our aim was to investigate how the COMT Val158Met may contribute to phenotypic variation in clinical diagnosis using sad facial affect processing as a probe for its neural action. Method - We employed functional magnetic resonance imaging to measure activation in the amygdala, ventromedial PFC (vmPFC) and ventrolateral PFC (vlPFC) during sad facial affect processing in family members with BD (n=40), MDD and anxiety disorders (n=22) or no psychiatric diagnosis (n=25) and 50 healthy controls. Results - Irrespective of clinical phenotype, the Val158 allele was associated with greater amygdala activation and the Met allele with greater signal change in the vmPFC and vlPFC. Signal changes in the amygdala and vmPFC were not associated with disease expression. However, in the right vlPFC the Met158 allele was associated with greater activation in all family members with affective morbidity compared with relatives without a psychiatric diagnosis and healthy controls. Conclusions - Our results suggest that the COMT Val158Met polymorphism has a pleiotropic effect within the neural networks subserving emotional processing. Furthermore the Met158 allele further reduces cortical efficiency in the vlPFC in individuals with affective morbidity. © 2010 Cambridge University Press.

Setting up a bioreactor for recombinant protein production in yeast

Scale-up from shake flasks to bioreactors allows for the more reproducible, high-yielding production of recombinant proteins in yeast. The ability to control growth conditions through real-time monitoring facilitates further optimization of the process. The setup of a 3-L stirred-tank bioreactor for such an application is described. © 2012 Springer Science+business Media, LLC.

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.

Studies in fungal biology

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Adaptive electrical signal post-processing in optical communications systems

Improving bit error rates in optical communication systems is a difficult and important problem. The error correction must take place at high speed and be extremely accurate. We show the feasibility of using hardware implementable machine learning techniques. This may enable some error correction at the speed required.

Pre-attentive auditory sensory processing in autistic spectrum disorder:are electromagnetic measurements telling us a coherent story?

Sensory processing is a crucial underpinning of the development of social cognition, a function which is compromised in variable degree in patients with pervasive developmental disorders (PDD). In this manuscript, we review some of the most recent and relevant contributions, which have looked at auditory sensory processing derangement in PDD. The variability in the clinical characteristics of the samples studied so far, in terms of severity of the associated cognitive deficits and associated limited compliance, underlying aetiology and demographic features makes a univocal interpretation arduous. We hypothesise that, in patients with severe mental deficits, the presence of impaired auditory sensory memory as expressed by the mismatch negativity could be a non-specific indicator of more diffuse cortical deficits rather than causally related to the clinical symptomatology. More consistent findings seem to emerge from studies on less severely impaired patients, in whom increased pitch perception has been interpreted as an indicator of increased local processing, probably as compensatory mechanism for the lack of global processing (central coherence). This latter hypothesis seems extremely attractive and future trials in larger cohorts of patients, possibly standardising the characteristics of the stimuli are a much-needed development. Finally, specificity of the role of the auditory derangement as opposed to other sensory channels needs to be assessed more systematically using multimodal stimuli in the same patient group. (c) 2006 Elsevier B.V. All rights reserved.

Process and performance in international collaborative research

Motivated by policy goals to develop international research capability and our experiences of collaborative research, we wanted to learn more about the factors that influence success in collaborative research. This article presents a review of the academic literature on collaborative research, focusing on multinational teams doing international comparative research. We address the question ‘what accounts for variation in process and performance of collaborative research projects?’, through 11 themes: context; vision; reward and commitment; leadership; structure; contract; task capability; sociability; communication; finance; rhythm and pace. We then propose an agenda for future research with an analytic framework and, finally, our conclusions.

Immunoinformatics and the in silico prediction of immunogenicity:an introduction

Immunoinformatics is the application of informatics techniques to molecules of the immune system. One of its principal goals is the effective prediction of immunogenicity, be that at the level of epitope, subunit vaccine, or attenuated pathogen. Immunogenicity is the ability of a pathogen or component thereof to induce a specific immune response when first exposed to surveillance by the immune system, whereas antigenicity is the capacity for recognition by the extant machinery of the adaptive immune response in a recall response. In thisbook, we introduce these subjects and explore the current state of play in immunoinformatics and the in silico prediction of immunogenicity.

Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity:in silico bioinformatic step-by-step guide using quantitative structure-activity relationships

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.

In silico prediction of peptide-MHC binding affinity using SVRMHC

The binding between peptide epitopes and major histocompatibility complex (MHC) proteins is a major event in the cellular immune response. Accurate prediction of the binding between short peptides and class I or class II MHC molecules is an important task in immunoinformatics. SVRMHC which is a novel method to model peptide-MHC binding affinities based on support rector machine regression (SVR) is described in this chapter. SVRMHC is among a small handful of quantitative modeling methods that make predictions about precise binding affinities between a peptide and an MHC molecule. As a kernel-based learning method, SVRMHC has rendered models with demonstrated appealing performance in the practice of modeling peptide-MHC binding.

Molecular dynamics simulations:bring biomolecular structures alive on a computer

The molecular dynamics (MD) simulations play a very important role in science today. They have been used successfully in binding free-energy calculations and rational design of drugs and vaccines. MD simulations can help visualize and understand structures and dynamics at an atomistic level when combined with molecular graphics programs. The molecular and atomistic properties can be displayed on a computer in a time-dependent way, which opens a road toward a better understanding of the relationship of structure, dynamics, and function. In this chapter, the basics of MD are explained, together with a step-by-step description of setup and running an MD simulation.

Metallocene ethylene-1-octene copolymers:influence of comonomer content on thermo-mechanical, rheological, and thermo-oxidative behaviours before and after melt processing in an internal mixer

The influence of the comonomer content in a series of metallocene-based ethylene-1-octene copolymers (m-LLDPE) on thermo-mechanical, rheological, and thermo-oxidative behaviours during melt processing were examined using a range of characterisation techniques. The amount of branching was calculated from 13C NMR and studies using differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) were employed to determine the effect of short chain branching (SCB, comonomer content) on thermal and mechanical characteristics of the polymer. The effect of melt processing at different temperatures on the thermo-oxidative behaviour of the polymers was investigated by examining the changes in rheological properties, using both melt flow and capillary rheometry, and the evolution of oxidation products during processing using infrared spectroscopy. The results show that the comonomer content and catalyst type greatly affect thermal, mechanical and oxidative behaviour of the polymers. For the metallocene polymer series, it was shown from both DSC and DMA that (i) crystallinity and melting temperatures decreased linearly with comonomer content, (ii) the intensity of the ß-transition increased, and (iii) the position of the tan δmax peak corresponding to the a-transition shifted to lower temperatures, with higher comonomer content. In contrast, a corresponding Ziegler polymer containing the same level of SCB as in one of the m-LLDPE polymers, showed different characteristics due to its more heterogeneous nature: higher elongational viscosity, and a double melting peak with broader intensity that occurred at higher temperature (from DSC endotherm) indicating a much broader short chain branch distribution. The thermo-oxidative behaviour of the polymers after melt processing was similarly influenced by the comonomer content. Rheological characteristics and changes in concentrations of carbonyl and the different unsaturated groups, particularly vinyl, vinylidene and trans-vinylene, during processing of m-LLDPE polymers, showed that polymers with lower levels of SCB gave rise to predominantly crosslinking reactions at all processing temperatures. By contrast, chain scission reactions at higher processing temperatures became more favoured in the higher comonomer-containing polymers. Compared to its metallocene analogue, the Ziegler polymer showed a much higher degree of crosslinking at all temperatures because of the high levels of vinyl unsaturation initially present.