Molecular genetics of X-linked cone-rod dystrophy and Åland Island eye disease

Inherited retinal diseases are the most common cause of vision loss among the working population in Western countries. It is estimated that ~1 of the people worldwide suffer from vision loss due to inherited retinal diseases. The severity of these diseases varies from partial vision loss to total blindness, and at the moment no effective cure exists. To date, nearly 200 mapped loci, including 140 cloned genes for inherited retinal diseases have been identified. By a rough estimation 50% of the retinal dystrophy genes still await discovery. In this thesis we aimed to study the genetic background of two inherited retinal diseases, X-linked cone-rod dystrophy and Åland Island eye disease. X-linked cone-rod dystrophy (CORDX) is characterized by progressive loss of visual function in school age or early adulthood. Affected males show reduced visual acuity, photophobia, myopia, color vision defects, central scotomas, and variable changes in fundus. The disease is genetically heterogeneous and two disease loci, CORDX1 and CORDX2, were known prior to the present thesis work. CORDX1, located on Xp21.1-11.4, is caused by mutations in the RPGR gene. CORDX2 is located on Xq27-28 but the causative gene is still unknown. Åland Island eye disease (AIED), originally described in a family living in Åland Islands, is a congenital retinal disease characterized by decreased visual acuity, fundus hypopigmentation, nystagmus, astigmatism, red color vision defect, myopia, and defective night vision. AIED shares similarities with another retinal disease, congenital stationary night blindness (CSNB2). Mutations in the L-type calcium channel α1F-subunit gene, CACNA1F, are known to cause CSNB2, as well as AIED-like disease. The disease locus of the original AIED family maps to the same genetic interval as the CACNA1F gene, but efforts to reveal CACNA1F mutations in patients of the original AIED family have been unsuccessful. The specific aims of this study were to map the disease gene in a large Finnish family with X-linked cone-rod dystrophy and to identify the disease-causing genes in the patients of the Finnish cone-rod dystrophy family and the original AIED family. With the help of linkage and haplotype analyses, we could localize the disease gene of the Finnish cone-rod dystrophy family to the Xp11.4-Xq13.1 region, and thus establish a new genetic X-linked cone-rod dystrophy locus, CORDX3. Mutation analyses of candidate genes revealed three novel CACNA1F gene mutations: IVS28-1 GCGTC>TGG in CORDX3 patients, a 425 bp deletion, comprising exon 30 and flanking intronic regions in AIED patients, and IVS16+2T>C in an additional Finnish patient with a CSNB2-like phenotype. All three novel mutations altered splice sites of the CACNA1F gene, and resulted in defective pre-mRNA splicing suggesting altered or absent channel function as a disease mechanism. The analyses of CACNA1F mRNA also revealed novel alternative wt splice variants, which may enhance channel diversity or regulate the overall expression level of the channel. The results of our studies may be utilized in genetic counseling of the families, and they provide a basis for studies on the pathogenesis of these diseases. In the future, the knowledge of the genetic defects may be used in the identification of specific therapies for the patients.

Carbon sequestration versus bioenergy: A case study from South India exploring the relative land-use efficiency of two options for climate change mitigation

This case study has been carried out as a comparison between two different land-use strategies for climate change mitigation, with possible application within the Clean Development Mechanisms. The benefits of afforestation for carbon sequestration versus for bioenergy production are compared in the context of development planning to meet increasing domestic and agricultural demand for electricity in Hosahalli village, Karnataka, India. One option is to increase the local biomass based electricity generation, requiring an increased biomass plantation area. This option is compared with fossil based electricity generation where the area is instead used for producing wood for non-energy purposes while also sequestering carbon in the soil and standing biomass. The different options have been assessed using the PRO-COMAP model. The ranking of the different options varies depending on the system boundaries and time period. Results indicate that, in the short term (30 years) perspective, the mitigation potential of the long rotation plantation is largest, followed by the short rotation plantation delivering wood for energy. The bioenergy option is however preferred if a long-term view is taken. Short rotation forests delivering wood for short-lived non-energy products have the smallest mitigation potential, unless a large share of the wood products are used for energy purposes (replacing fossil fuels) after having served their initial purpose. If managed in a sustainable manner all of these strategies can contribute to the improvement of the social and environmental situation of the local community. (C) 2009 Elsevier Ltd. All rights reserved.

Snow characteristics in Dronning Maud Land, Antarctica

Snow cover is very sensitive to climate change and has a large feedback effect on the climate system due to the high albedo. Snow covers almost all surfaces in Antarctica and small changes in snow properties can mean large changes in absorbed radiation. In the ongoing discussion of climatic change, the mass balance of Antarctica has received increasing focus during recent decades, since its reaction to global warming strongly influences sea-level change. The aim of the present work was to examine the spatial and temporal variations in the physical and chemical characteristics of surface snow and annual accumulation rates in western Dronning Maud Land, Antarctica. The data were collected along a 350-km-long transect from the coast to the plateau during the years 1999-2004 as a part of the Finnish Antarctic Research Programme (FINNARP). The research focused on the most recent annual accumulation in the coastal area. The results show that the distance from the sea, and the moisture source, was the most predominant factor controlling the variations in both physical (conductivity, grain size, oxygen isotope ratio and accumulation) and chemical snow properties. The sea-salt and sulphur-containing components predominated in the coastal region. The local influences of nunataks and topographic highs were also visible on snow. The variations in all measured properties were wide within single sites mostly due to redistribution by winds and sastrugi topography, which reveals the importance of the spatially representative measurements. The mean accumulations occurred on the ice shelf, in the coastal region and on the plateau: 312 ± 28, 215 ± 43 and 92 ± 25 mm w.e., respectively. Depth hoar layers were usually found under the thin ice crust and were associated with a low dielectric constant and high concentrations of nitrate. Taking into account the vast size of the Antarctic ice sheet and its geographic characteristics, it is important to extend investigation of the distribution of surface snow properties and accumulation to provide well-documented data.

Urban growth dilemmas and solutions in China: Looking forward to 2030

China’s urbanization and industrialization are occupying farmland in large amounts, which is strongly driven by land finance regime. This is due to the intensified regional/local competition for manufacturing investment opportunities that push local governments to expropriate farmland at low prices while lease land at high market value to property developers. The additional revenue obtained in this way, termed financial increment in land values, can drive local economic growth, and provide associated infrastructure and other public services. At the same time, however, a floating population of large numbers of inadequately compensated land-lost farmers, although unable to become citizens, have to migrate into the urban areas for work, causing overheated employment and housing markets, with rocketing unaffordable housing prices. This, together with various micro factors relating to the party/state’s promotion/evaluation system play an essential role leading to some serious economic, environment and social consequences, e.g., on migrant welfare, the displacement of peasants and the loss of land resources that requires immediate attention. Our question is: whether such type of urbanization is sustainable? What are the mechanisms behind such a phenomenal urbanization process? From the perspective of institutionalism, this paper aims to investigate the institutional background of the urban growth dilemma and solutions in urban China and to introduce further an inter-regional game theoretical framework to indicate why the present urbanization pattern is unsustainable. Looking forward to 2030, paradigm policy changes are made from the triple consideration of floating population, social security and urban environmental pressures. This involves: (1) changing land increment based finance regime into land stock finance system; (2) the citizenization of migrant workers with affordable housing, and; (3) creating a more enlightened local government officer appraisal system to better take into account societal issues such as welfare and beyond.

Impact of riparian land use on stream insects of Kudremukh National Park, Karnataka state, India

The impact of riparian land use on the stream insect communities was studied at Kudremukh National Park located within Western Ghats, a tropical biodiversity hotspot in India. The diversity and community composition of stream insects varied across streams with different riparian land use types. The rarefied family and generic richness was highest in streams with natural semi evergreen forests as riparian vegetation. However, when the streams had human habitations and areca nut plantations as riparian land use type, the rarefied richness was higher than that of streams with natural evergreen forests and grasslands. The streams with scrub lands and iron ore mining as the riparian land use had the lowest rarefied richness. Within a landscape, the streams with the natural riparian vegetation had similar community composition. However, streams with natural grasslands as the riparian vegetation, had low diversity and the community composition was similar to those of paddy fields. We discuss how stream insect assemblages differ due to varied riparian land use patterns, reflecting fundamental alterations in the functioning of stream ecosystems. This understanding is vital to conserve, manage and restore tropical riverine ecosystems.

Assessing the mitigation potential of forestry activities in a changing climate: A case study for Karnataka

The Clean Development Mechanism (CDM), Article 12 of the Kyoto Protocol allows Afforestation and Reforestation (A/R) projects as mitigation activities to offset the CO2 in the atmosphere whilst simultaneously seeking to ensure sustainable development for the host country. The Kyoto Protocol was ratified by the Government of India in August 2002 and one of India's objectives in acceding to the Protocol was to fulfil the prerequisites for implementation of projects under the CDM in accordance with national sustainable priorities. The objective of this paper is to assess the effectiveness of using large-scale forestry projects under the CDM in achieving its twin goals using Karnataka State as a case study. The Generalized Comprehensive Mitigation Assessment Process (GCOMAP) Model is used to observe the effect of varying carbon prices on the land available for A/R projects. The model is coupled with outputs from the Lund-Potsdam-Jena (LPJ) Dynamic Global Vegetation Model to incorporate the impacts of temperature rise due to climate change under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2, A1B and B1. With rising temperatures and CO2, vegetation productivity is increased under A2 and A1B scenarios and reduced under B1. Results indicate that higher carbon price paths produce higher gains in carbon credits and accelerate the rate at which available land hits maximum capacity thus acting as either an incentive or disincentive for landowners to commit their lands to forestry mitigation projects. (C) 2009 Elsevier B.V. All rights reserved.

Road kills of amphibians in different land use areas from Sharavathi river basin, central Western Ghats, India

A survey of amphibian mortality on roads was carried out in the Sharavathi river basin in the central Western Ghats. Road kills in three different land use areas: agricultural fields, water bodies and forests were recorded for four days along three 100m stretches in each type of area. One-hundred-and-forty-four individuals belonging to two orders, eight families, 11 genera and 13 species were recorded in the survey. Kills/km observed were: in forest 55, agricultural fields 38 and water bodies 27, for an overall average of 40 kills/km. Kill species compositions varied significantly between land use areas, but not overall kill rates.

Topics in Spatial Econometrics - With Applications to House Prices

Topics in Spatial Econometrics — With Applications to House Prices Spatial effects in data occur when geographical closeness of observations influences the relation between the observations. When two points on a map are close to each other, the observed values on a variable at those points tend to be similar. The further away the two points are from each other, the less similar the observed values tend to be. Recent technical developments, geographical information systems (GIS) and global positioning systems (GPS) have brought about a renewed interest in spatial matters. For instance, it is possible to observe the exact location of an observation and combine it with other characteristics. Spatial econometrics integrates spatial aspects into econometric models and analysis. The thesis concentrates mainly on methodological issues, but the findings are illustrated by empirical studies on house price data. The thesis consists of an introductory chapter and four essays. The introductory chapter presents an overview of topics and problems in spatial econometrics. It discusses spatial effects, spatial weights matrices, especially k-nearest neighbours weights matrices, and various spatial econometric models, as well as estimation methods and inference. Further, the problem of omitted variables, a few computational and empirical aspects, the bootstrap procedure and the spatial J-test are presented. In addition, a discussion on hedonic house price models is included. In the first essay a comparison is made between spatial econometrics and time series analysis. By restricting the attention to unilateral spatial autoregressive processes, it is shown that a unilateral spatial autoregression, which enjoys similar properties as an autoregression with time series, can be defined. By an empirical study on house price data the second essay shows that it is possible to form coordinate-based, spatially autoregressive variables, which are at least to some extent able to replace the spatial structure in a spatial econometric model. In the third essay a strategy for specifying a k-nearest neighbours weights matrix by applying the spatial J-test is suggested, studied and demonstrated. In the final fourth essay the properties of the asymptotic spatial J-test are further examined. A simulation study shows that the spatial J-test can be used for distinguishing between general spatial models with different k-nearest neighbours weights matrices. A bootstrap spatial J-test is suggested to correct the size of the asymptotic test in small samples.

Cobreaking of Stock Prices and Contagion

Financial crises have shown that dramatic movements in one financial market can have a powerful impact on other markets. The paper proposes to use cobreaking to model comovements between financial markets during crises and to test for conta-gion. It finds evidence of cobreaking between stock returns in developed markets. Finding cobreaking has implications for the diversification of international investments. For emerging mar-ket stock returns the evidence of cobreaking is mainly due to the non-financial event of the 9/11 terrorist attacks in 2001. Fi-nancial crises originating in one emerging market do not spread to other markets, i.e., no contagion.

An Empirical Study of the Mixture of Time and Movements in Prices

This paper investigates the persistent pattern in the Helsinki Exchanges. The persistent pattern is analyzed using a time and a price approach. It is hypothesized that arrival times are related to movements in prices. Thus, the arrival times are defined as durations and formulated as an Autoregressive Conditional Duration (ACD) model as in Engle and Russell (1998). The prices are defined as price changes and formulated as a GARCH process including duration measures. The research question follows from market microstructure predictions about price intensities defined as time between price changes. The microstructure theory states that long transaction durations might be associated with both no news and bad news. Accordingly, short durations would be related to high volatility and long durations to low volatility. As a result, the spread will tend to be larger under intensive moments. The main findings of this study are 1) arrival times are positively autocorrelated and 2) long durations are associated with low volatility in the market.

Learning dynamic prices in multiseller electronic retail markets with price sensitive customers, stochastic demands, and inventory replenishments

In this paper, we use reinforcement learning (RL) as a tool to study price dynamics in an electronic retail market consisting of two competing sellers, and price sensitive and lead time sensitive customers. Sellers, offering identical products, compete on price to satisfy stochastically arriving demands (customers), and follow standard inventory control and replenishment policies to manage their inventories. In such a generalized setting, RL techniques have not previously been applied. We consider two representative cases: 1) no information case, were none of the sellers has any information about customer queue levels, inventory levels, or prices at the competitors; and 2) partial information case, where every seller has information about the customer queue levels and inventory levels of the competitors. Sellers employ automated pricing agents, or pricebots, which use RL-based pricing algorithms to reset the prices at random intervals based on factors such as number of back orders, inventory levels, and replenishment lead times, with the objective of maximizing discounted cumulative profit. In the no information case, we show that a seller who uses Q-learning outperforms a seller who uses derivative following (DF). In the partial information case, we model the problem as a Markovian game and use actor-critic based RL to learn dynamic prices. We believe our approach to solving these problems is a new and promising way of setting dynamic prices in multiseller environments with stochastic demands, price sensitive customers, and inventory replenishments.