Dan Lundh

Vitamin D and prostate cancer: The role of membrane initiated signaling pathways in prostate cancer progression

1,25-Dihydroxyvitamin D3 (1,25(OH)2D3) has been demonstrated to mediate both genomic and non-genomic responses in prostate cancer (CaP) cells. Here, we give an overview of membrane initiated 1,25(OH)2D3 signaling in prostate cancer cell progression. The presence of PDIA3 was investigated and homologous modeling of the putative PDIA3 receptor complex was conducted. Furthermore, the cellular distribution of nVDR was analyzed. We could show that both nVDR and PDIA3 are expressed in the prostate cancer cell lines investigated. The homologous modeling of PDIA3 showed that the receptor complex exists in a trimer formation, which suggests for allosteric activity. Our findings support previous reports and suggest that 1,25(OH)2D3 is an important therapeutic agent in inhibiting prostate cancer progression. Furthermore, our data show that 1,25(OH)2D3 regulate prostate cell biology via multiple pathways and targeting specific pathways for 1,25(OH)2D3 might provide more effective therapies compared to the vitamin D therapies currently clinically tested.

Bioinformatics in studies of SDR and MDR enzymes.

Bioinformatics utilises information in databases to understand biological processes and interpret experimental data. Methods include sequence comparisons, structural and functional predictions, and molecular modelling. Applied to the families of short-chain and medium-chain dehydrogenases/reductases (SDR and MDR), much information is obtained.

A Kinetic Model on Calcium Residues and Facilitation

The role of calcium as a regulator for neuronal function is very important. Calcium initiates many reactions that determine the behavior of the neuronal cell. In this article we use a kinetic model of the presynaptic synapsin I protein. This protein is responsible, via phosphorylation, for regulating the amount of transmitter vesicles available for release. This protein has been shown to inhibit the amount of vesicles ready for release in its dephosphorylated state, and releases its inhibitory binding due to phosphorylation. The phosphorylation of synapsin I depends on cyclic adenosine monophosphate and type II calcium/calmodulin protein kinase. Due to the duration of these two second messengers, we show that short-term facilitation does not have to depend on calcium residues. Furthermore, we show that calcium residues (in parts of microM range) promote increased facilitation due to the additional calcium reacting with the second messenger system.

Modeling Arsenic Accumulation in Plants

Rice growing regions plagued by arsenic-contaminated soils and irrigation water do not have a viable option for producing arsenic-free crops. For instance, in Bangladesh every year more than 30 million people are affected from rice-derived arsenic contamination that contributes to arsenic levels known to cause health-related illnesses. Our strategy is to genetically-modify molecular mechanisms involved in the localization of arsenic to divert it to the non-edible parts of the plant. To identify viable candidate genes, we employed data mining, an in silico analysis based on searching existing genomic databases and in the genetic model plant Arabidopsis thaliana. To assist our investigation, we constructed a kinetic model to outline strategies for developing genetically-modified plants exhibiting a significant reduction in arsenic concentration in the edible parts (straw and grain). This model contains equations for uptake, metabolism and sequestration of different types of arsenic (As (V), As (III,) MMAA and DMAA). The model was implemented using XPP and validated against existing data from the literature. From these analyses, we identified four candidate genes that are involved either in uptake, transport or cellular localization of arsenic in plants. But we found only one gene implicated in arsenic metabolism in rice. In parallel, we identified available T-DNA insertion mutants to determine the effects of these genes on arsenic accumulation. Results obtained from in silico data-mining, kinetic modeling, and assays with T-DNA insertion mutants will be used to design gene cloning experiments to study the target genes in yeast, E. coli, and Arabidopsis heterologous systems. Upon confirmation of the effectiveness of these candidates, vectors containing the target genes will be constructed for transformation into rice. The new rice varieties produced will be tested under field conditions to assess their effectiveness at reducing or eliminating arsenic from the edible parts of the rice plant.

On Synaptic Plasticity: Modelling Molecular Kinases involved in Transmitter Release

The neurotransmitter release depends, in principal, on two neuronal events. One is the influx of Calcium in the active zone due to polarization, and the other is the amount of fusion available neurotransmitter vesicles. We state a model of the phosphorylation of the Synapsins (I and II), which creates a pool of fusion available vesicles. The exocytosis of vesicles is stated by Calcium on and off rates, modelling the complex of the fusion pore. The aim here is to model paired pulse facilitation due to phosphorylation of the Synapsins, and post-tetanic potentiation due to increased kinetic activity of the cAMP complex. In addition we show that the regulation of fusion competent vesicles in post-tetanic potentiation is highly correlated to Calcium residues released by organelles, i.e Calcium buffering.

On Methods for Combination of Results from Gene-Finding Programs for Improved Prediction Accuracy

Gene-finding programs available today give far from 100% correct predictions. The idea of combining a number of different gene-finding programs to achieve an improved overall prediction accuracy was recently brought forward. Murakami and Takagi [1] published the first attempt to combine results from different gene-finding programs. Their discrete combination methods based on logical expressions showed improved prediction accuracy (by 3-5 %) compared to the best performing individual program (GENSCAN).

Systematicity in IH-analysis

AI researchers can agree that any non-trivial cognitive system must be able to represent complex structured items. A complex structured item is typically seen to be built up systematically from parts drawn from a determinate set. The process by which such parts are combined to form complex structured items is called the mode of composition.