Pneumococcal meningitis causes accumulation of neurotoxic kynurenine metabolites in brain regions prone to injury

Pneumococcal meningitis (PM) is characterized by an intense inflammatory host reaction that contributes to the development of cortical necrosis and hippocampal apoptosis. Inflammatory conditions in the brain are known to induce tryptophan degradation along the kynurenine pathway, resulting in accumulation of neurotoxic metabolites. In the present study, we investigated the contribution of the kynurenine pathway to brain injury in experimental PM by measuring the concentration of its metabolites and the enzymatic activities and mRNA levels of its major enzymes in the vulnerable brain regions. In the late phase of acute PM, we found a significant transcriptional upregulation of kynurenine-3-hydroxylase and an accumulation of the neurotoxic metabolites 3-hydroxykynurenine (3-HKYN) and 3-hydroxyanthranilic acid in cortex and hippocampus. The positive correlation between the concentration of 3-HKYN and the extent of hippocampal apoptosis adds support to the concept that 3-HKYN contributes to brain injury in PM.

Climate change in mountain regions: how local communities adapt to extreme events

This paper examines how local communities adapt to climate change and how governance structures can foster or undermine adaptive capacity. Climate change policies, in general, and disaster risk management in mountain regions, in particular, are characterised by their multi-level and multi-sectoral nature during formulation and implementation. The involvement of numerous state and non-state actors at local to national levels produces a variety of networks of interaction and communication. The paper argues that the structure of these relational patterns is critical for understanding adaptive capacity. It thus proposes an expanded concept of adaptive capacity that incorporates (horizontal and vertical) actor integration and communication flow between these actors. The paper further advocates the use of formal social network analysis to assess these relational patterns. Preliminary results from research on adaptation to climate change in a Swiss mountain region vulnerable to floods and other natural hazards illustrate the conceptual and empirical significance of the main arguments.

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.

Reducing the global burden of depression : population level analysis of intervention cost-effectiveness in 14 world regions

International evidence on the cost and effects of interventions for reducing the global burden of depression remain scarce. Aims: To estimate the population-level cost-effectiveness of evidence-based depression interventions and their contribution towards reducing current burden. Method: Primary-care-based depression interventions were modelled at the level of whole populations in 14 epidemiological subregions of the world. Total population-level costs (in international dollars or I$) and effectiveness (disability adjusted life years (DALYs) averted) were combined to form average and incremental cost-effectiveness ratios. Results: Evaluated interventions have the potential to reduce the current burden of depression by 10–30%. Pharmacotherapy with older antidepressant drugs, with or without proactive collaborative care, are currently more cost-effective strategies than those using newer antidepressants, particularly in lower-income subregions. Conclusions: Even in resource-poor regions, each DALYaverted by efficient depression treatments in primary care costs less than 1 year of average per capita income, making such interventions a cost-effective use of health resources. However, current levels of burden can only be reduced significantlyif there is a substantialincrease substantial increase intreatment coverage.

Urban sustainability and growth management in south-east Asian city-regions : the case of Kuala Lumpur and Hong Kong

Major South-East Asian city-regions have experienced considerable physical, economic and social transformations during the past three decades. The rapid pace of globalisation and economic restructuring has resulted in these city-regions receiving the full impact of urbanisation pressures. In an attempt to ease these pressures, city-regions such as Bangkok, Seoul, Tokyo, Taipei, Hong Kong, Singapore and Kuala Lumpur have advocate growth management approaches giving particular interest to urban sustainability. These approaches promote efforts to achieve the triple bottom line sustainability by balancing economic and social development, and environmental protection, and putting more emphasis on compact and optimum development of urban forms. This paper evaluates the case of two South-East Asian city-regions, Kuala Lumpur and Hong Kong, and assesses their experiences in managing their urban forms whilst promoting sustainable patterns of urban development. The findings show that sustainable urban development initiatives employing a top down approach has yielded encouraging results in these case study city-regions. However the need for a more concerted effort towards the overall sustainability agenda still remains vital.

Promoting sustainable urban development in fast growing city-regions : practices from Kuala Lumpur and Hong Kong

The Asia‐Pacific region is characterised by rapid population growth and urbanisation. These trends often result in an increasing consumption of land, which in turn lead to spatially expansive and discontinuous urban development. As a consequence, local communities and the environment face strong pressures. Many cities in the region have developed policies to tackle the issue of rapid growth and its associated consequences, for example climate change. The broad aim of this paper is to identify the nature, trends and strategies of growth management in major Asia‐Pacific city‐regions, and their implications for natural resource management and infrastructure provision. More specifically, this research seeks to provide insights on sustainable urban development practice, particularly on the promotion of compact urbanisation within the Asia‐Pacific’s fastest growing regions. The methodology of the paper includes a detailed literature review and a comparative analysis of existing strategies and policies. The literature review focuses on the key concepts related to sustainable urban growth management. It also includes existing applications of urban growth management approaches and planning information system in managing growth. Following the literature review, the paper undertakes a comparative analysis of the strategies of major Asia‐Pacific city‐regions of Kuala Lumpur and Hong Kong in terms of their approaches to sustainable urban development. The findings of the paper provide a clear understanding of the necessity of sustainable urban development practices. It contributes to the development of a substantial base for further research. Ultimately, this research aims to shed light on sustainable urban development by providing insights on the management of growth, natural resources and urban infrastructures.