Parenchymal and vascular Aβ-deposition and its effects on the degeneration of neurons and cognition in Alzheimer's disease

The deposition of the amyloid β-protein (Aβ) is one of the pathological hallmarks of Alzheimer's disease (AD). Aβ-deposits show the morphology of senile plaques and cerebral amyloid angiopathy (CAA). Senile plaques and vascular Aβ-deposits occur first in neocorti-cal areas. Then, they expand hierarchically into further brain regions. The distribution of Aβ plaques throughout the entire brain, thereby correlates with the clinical status of the patients. Imaging techniques for Aβ make use of the hierarchical distribution of Aβ to distinguish AD patients from non-AD patients. However, pathology seen in AD patients represents a late stage of a pathological process starting 10–30 years earlier in cognitively normal individuals. In addition to the fibrillar amyloid of senile plaques, oligomeric and monomeric Aβ is found in the brain. Recent studies revealed that oligomeric Aβ is presumably the most toxic Aβ-aggregate, which interacts with glutamatergic synapses. In doing so, dendrites are presumed to be the primary target for Aβ-toxicity. In addition, vascular Aβ-deposits can lead to capillary occlusion and blood flow disturbances presumably contributing to the alteration of neurons in addition to the direct neurotoxic effects of Aβ. All these findings point to an important role of Aβ and its aggregates in the neurodegenerative process of AD. Since there is already significant neuron loss in AD patients, treatment strategies aimed at reducing the amyloid load will presumably not cure the symptoms of dementia but they may stop disease progression. Therefore, it seems to be necessary to protect the brain from Aβ-toxicity already in stages of the disease with minor neuron loss before the onset of cognitive symptoms

Presence and localization of a 30-kDa basic fibroblast growth factor-like protein in rodent testes

We have used a recently characterized rabbit antiserum against basic fibroblast growth factor (bFGF), which recognizes various forms of bFGF, to examine the presence and localization of bFGF in the testes of adult rats and mice and the 5-day-old rat. In Western blots of testicular homogenates of adult rats and mice and immature rats, immunoreactive single bands at approximately 30 kDa were detected. Immunocytochemistry revealed specific staining restricted to the tubular compartment. In 5-day-old rat testes, prespermatogonia were immunoreactive. The cytoplasm of pachytene spermatocytes was heavily stained in the adult testes of both species. Staining of these cells became evident around stage IV/V, was prominent in stage VII through IX and declined about stage XII/XIII (rat) or X-XI (mouse). Staining was seen in type A spermatogonia and in elongating spermatids in their cytoplasmatic lobes and along their flagellae. Sertoli cells were unstained. We propose that the pluripotential growth factor bFGF could be involved in the regulation of germ cell proliferation and differentiation in the adult and immature testis

Spin-phonon coupling in antiferromagnetic chromium spinels

The temperature dependence of eigenfrequencies and intensities of the IR active modes has been investigated for the antiferromagnetic chromium spinel compounds CdCr2O4, ZnCr2O4, ZnCr2S4, ZnCr2Se4, and HgCr2S4 by IR spectroscopy for temperatures from 5 K to 300 K. At the transition into the magnetically ordered phases, and driven by spin-phonon coupling, most compounds reveal significant splittings of the phonon modes. This is true for geometrically frustrated CdCr2O4, and ZnCr2O4, for bond frustrated ZnCr2S4 and for ZnCr2Se4, which also is bond frustrated, but dominated by ferromagnetic exchange. The pattern of splitting is different for the different compounds and crucially depends on the nature of frustration and of the resulting spin order. HgCr2S4, which is almost ferromagnetic, exhibits no splitting of the eigenfrequencies, but shows significant shifts due to ferromagnetic spin fluctuations.Comment: 15 pages, 6 figure

Nanofiber-based optical trapping of cold neutral atoms

We present experimental techniques and results related to the optimization and characterization of our nanofiber-based atom trap [Vetsch et al., Phys. Rev. Lett. 104, 203603 (2010)]. The atoms are confined in an optical lattice which is created using a two-color evanescent field surrounding the optical nanofiber. For this purpose, the polarization state of the trapping light fields has to be properly adjusted. We demonstrate that this can be accomplished by analyzing the light scattered by the nanofiber. Furthermore, we show that loading the nanofiber trap from a magneto-optical trap leads to sub-Doppler temperatures of the trapped atomic ensemble and yields a sub-Poissonian distribution of the number of trapped atoms per trapping site

From Organisational Behaviour to Industrial Network Evolutions: Stimulating Sustainable Development of Bioenergy Networks in Emerging Economies

The aim of this thesis is to understand what drives the evolution of industrial networks and how such understanding can be used to stimulate sustainable development. A complex adaptive systems perspective has been adopted to analyse the complex interaction between organisational behaviour and industrial network evolution. This analysis has formed the basis for the development of a modelling approach that allows for quantitative exploration of how different organisational perceptions about current and future uncertainty affect their behaviour and therefore the network evolution. This analysis results in a set of potential evolutionary pathways for an industrial network and their associated performance in terms of sustainable development. Subsequently, this modelling approach has been used to explore the consequences of interventions in the network evolution and to identify robust interventions for stimulating sustainable development of industrial networks. The analysis, modelling approach and development of interventions has been developed in the context of a bioenergy network in the region of KwaZulu-Natal in South Africa. Industrial networks are an important aspect of today’s life and provide many goods and services to households and individuals all over the world. They consist of a large number of autonomous organisations, where some organisations contribute by transforming or transacting natural resources, such as oil, agricultural products or water, while other organisations contribute to networks by providing information or setting regulation or subsidies (local or national governments) or by influencing decision making processes of other organisations in networks (advocacy groups). Throughout the process from natural resource to product or service, industrial networks have important economic, environmental and social impacts on the socio-economic and biophysical systems in which they operate. The sum of complex interactions between organisations affects the rate in which natural resources are used, environmental impacts associated with transformation and transaction of resources and social impacts on local communities, regions or countries as a whole. The aim of this thesis is to understand how industrial networks evolve and how they can be stimulated towards sustainable development. The first question that has been addressed in this thesis is how to understand the complex interaction between organisational behaviour and industrial network evolution. Organisational behaviour is affected by many functional and implicit characteristics within the environment in which the organisation operates, while simultaneously the environment is a function of non-linear relationships between individual organisational actions and their consequences for both the function and structure of the network. This thesis has identified four different characteristics of industrial networks that affect organisational behaviour: 1) Functional characteristics 2) Implicit behavioural characteristics 3) Implicit relational characteristics 4) Implicit network characteristics. Functional characteristics are those characteristics that are formally recognised by all organisations within an industrial network and which affect their position within the network. Examples of functional characteristics are the price and quantity of resources available, the location and distance of organisations within a network, infrastructure availability or regulation. Implicit characteristics, on the other hand, are those characteristics that impact the decision making process of organisations, but which are not formally part of the network. From an organisational perspective, implicit characteristics are the rules, heuristics, norms and values that an organisation uses to determine its objectives, position and potential actions. Implicit relational characteristics, most importantly trust and loyalty, affect an organisations choice between potential partners and implicit network characteristics are those social norms and values that emerge through social embeddedness. Collectively, these functional and implicit characteristics and their interactions determine the outcome of organisational decisions and therefore the direction of the industrial network evolution. The complex interaction between these large numbers of characteristics requires quantitative models to explore how different network characteristics and different interactions result in different network evolutions. This thesis has developed an agent-based simulation model to explore industrial network evolutions. To represent the multi-scale complexity of industrial networks, the model consists of four scales. Each scale represents different processes that connect the functional and implicit characteristics of an industrial network to each other. The two basic scales represent the strategic actions of the organisations on the one hand and the industrial network function and structure on the other. The third scale represents the processes that take place within the mental models of organisations describing how they make sense of their environment and inform their strategic decision making process. The fourth scale represents the social embeddedness of organisations and how social processes create and destroy social institutions. The model has been developed such that it allows for exploring how changes in different network characteristics or processes affect the evolution of the network as a whole. The second question that has been addressed in this thesis is how to evaluate sustainable development of different evolutionary pathways of industrial networks. First of all, a systems approach has been adopted to explore the consequences of an industrial network to the larger socio-economic and biophysical system in which the network operates. Subsequently, a set of structural indicators has been proposed to evaluate the dynamic performance of industrial networks. These four structural indicators reflect the efficiency, effectiveness, resilience and adaptiveness of industrial networks. Efficiency and effectiveness relate to the operational features by which industrial networks provides a particular contribution to society. Resilience and adaptiveness relate to the system’s capacity to maintain or adapt its contribution to society while under stress of temporary shocks or permanent shifts, respectively. Finally, different multi-criteria decision analysis (MCDA) tools have been applied to provide a holistic evaluation of sustainable development of industrial networks. The third important question that is addressed in this thesis is how to systematically explore the potential evolutionary pathways of an industrial network, which has led to the development of agent-based scenario analysis. Agent-based scenario analysis systematically explores how industrial network evolutions might evolve depending on the perceptions of organisations towards the inherent uncertainty associated with strategic decision making in networks. The agent-based scenario analysis consists of two steps. Firstly, analysts develop a set of coherent context scenarios, which represents their view on the context in which an industrial network will operate within the future. For a bioenergy network, for example, this step results in a set of scenarios that each represent a coherent future of the socio-economic system in which the network might evolve. The second step is the development of a set of ‘agent scenarios’. Each agent-based scenario is based on a different ‘mental model’ employed by organisations within the network about how to deal with the inherent ambiguity of the future. The organisational perspective towards uncertainty is of major importance for the evolution of industrial networks, because it determines the innovative behaviour of organisations, the structure of the network and the direction in which the network evolves. One the one hand, organisations can ignore future ambiguity and base their actions on the environment that they can observe in their present state. On the other extreme, organisations can adopt a view that the future is inherently uncertain and in which they view social norms and values more important than functional characteristics to make sense of their environment. The mental models are differentiated according to two dimensions: 1) different mental representation of the world and 2) different cognitive processes that can be employed to inform strategic actions. Along these dimensions, different processes can be employed to make sense of the environment and to inform decision making. The thesis has shown that by systematically exploring the different perceptions possible, an adequate understanding of the different evolutionary pathways can be gained to inform the evaluation and development of interventions to stimulate sustainable development. The final part of this thesis has applied the analysis and methodology developed throughout this thesis to a bioenergy network in the province of Kwazulu-Natal in South Africa. The bioenergy network consists of a set of existing sugar mills with large quantities of bagasse, a biomass waste product, available. Bagasse is currently burned inefficiently to produce steam for the sugar mills, but can potentially be used for the production of green electricity, biodiesel, bioethanol or gelfuel. All of these products have important consequences for the region in terms of associated reductions in CO2 emissions, electrification of and/or energy provision for rural households and local economic development of the region. This thesis has modelled strategic decisions of the sugar mills, the existing electricity generator, potential independent energy producers, local and national governments and how their actions and interactions can lead to different evolutionary pathways of the bioenergy network. The agent-based scenario analysis has been used to explore how different perceptions of organisations can lead to different network evolutions. Finally, the model has been used to explore the consequences of two categories of interventions on stimulating sustainable development. The conclusions are that both categories of interventions, financial interventions by national government and the introduction of multi-criteria decision analysis (MCDA) tools to aid strategic decision making, can have both positive and negative effects on the network evolutions, depending on what ‘mental models’ are employed by organisations. Furthermore, there is no single intervention that outperforms the others in terms of stimulating both functional and structural features of sustainable development. The final conclusion is that instead of focusing on individual or collective targets, emphasis should be placed on the development of interventions that focus on evolutionary aspects of industrial networks rather than functional performance criteria. This thesis has also highlighted interesting research questions for future investigation. The methodology developed in this thesis is applied to a single case study, but there are still many questions concerning how different industrial networks might benefit from different organisational perceptions towards uncertainty. Furthermore, the role between the mental models and sustainable development requires further investigation, especially in the light of globalisation and the interconnectiveness of industrial networks in different countries and continents. Finally, this methodology has provided a platform for investigating how new technologies might be developed that anticipate needs of future generations. This thesis has provided a first and important step in developing a methodology that addresses the complex issues associated with sustainable development, benefiting both academics and practitioners that aim to stimulate sustainable development