Simvastatin decreases the level of heparin-binding protein in patients with acute lung injury

Background: Heparin-binding protein is released by neutrophils during inflammation and disrupts the integrity of the alveolar and capillary endothelial barrier implicated in the development of acute lung injury and systemic organ failure. We sought to investigate whether oral administration of simvastatin to patients with acute lung injury reduces plasma heparin-binding protein levels and improves intensive care unit outcome. Methods: Blood samples were collected from patients with acute lung injury with 48 h of onset of acute lung injury (day 0), day 3, and day 7. Patients were given placebo or 80 mg simvastatin for up to 14 days. Plasma heparin-binding protein levels from patients with acute lung injury and healthy volunteers were measured by ELISA. Results: Levels of plasma heparin-binding protein were significantly higher in patients with acute lung injury than healthy volunteers on day 0 (p = 0.011). Simvastatin 80 mg administered enterally for 14 days reduced plasma level of heparin-binding protein in patients. Reduced heparin-binding protein was associated with improved intensive care unit survival. Conclusions: A reduction in heparin-binding protein with simvastatin is a potential mechanism by which the statin may modify outcome from acute lung injury

DeBi: Discovering Differentially Expressed Biclusters using a Frequent Itemset Approach

<p>Abstract</p> <p>Background</p> <p>The analysis of massive high throughput data via clustering algorithms is very important for elucidating gene functions in biological systems. However, traditional clustering methods have several drawbacks. Biclustering overcomes these limitations by grouping genes and samples simultaneously. It discovers subsets of genes that are co-expressed in certain samples. Recent studies showed that biclustering has a great potential in detecting marker genes that are associated with certain tissues or diseases. Several biclustering algorithms have been proposed. However, it is still a challenge to find biclusters that are significant based on biological validation measures. Besides that, there is a need for a biclustering algorithm that is capable of analyzing very large datasets in reasonable time.</p> <p>Results</p> <p>Here we present a fast biclustering algorithm called DeBi (Differentially Expressed BIclusters). The algorithm is based on a well known data mining approach called frequent itemset. It discovers maximum size homogeneous biclusters in which each gene is strongly associated with a subset of samples. We evaluate the performance of DeBi on a yeast dataset, on synthetic datasets and on human datasets.</p> <p>Conclusions</p> <p>We demonstrate that the DeBi algorithm provides functionally more coherent gene sets compared to standard clustering or biclustering algorithms using biological validation measures such as Gene Ontology term and Transcription Factor Binding Site enrichment. We show that DeBi is a computationally efficient and powerful tool in analyzing large datasets. The method is also applicable on multiple gene expression datasets coming from different labs or platforms.</p

Semantic integration to identify overlapping functional modules in protein interaction networks

<p>Abstract</p> <p>Background</p> <p>The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms.</p> <p>Results</p> <p>We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO) annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches.</p> <p>Conclusion</p> <p>The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.</p

Multi-agent modeling of the South Korean avian influenza epidemic

<p>Abstract</p> <p>Background</p> <p>Several highly pathogenic avian influenza (AI) outbreaks have been reported over the past decade. South Korea recently faced AI outbreaks whose economic impact was estimated to be 6.3 billion dollars, equivalent to nearly 50% of the profit generated by the poultry-related industries in 2008. In addition, AI is threatening to cause a human pandemic of potentially devastating proportions. Several studies show that a stochastic simulation model can be used to plan an efficient containment strategy on an emerging influenza. Efficient control of AI outbreaks based on such simulation studies could be an important strategy in minimizing its adverse economic and public health impacts.</p> <p>Methods</p> <p>We constructed a spatio-temporal multi-agent model of chickens and ducks in poultry farms in South Korea. The spatial domain, comprised of 76 (37.5 km × 37.5 km) unit squares, approximated the size and scale of South Korea. In this spatial domain, we introduced 3,039 poultry flocks (corresponding to 2,231 flocks of chickens and 808 flocks of ducks) whose spatial distribution was proportional to the number of birds in each province. The model parameterizes the properties and dynamic behaviors of birds in poultry farms and quarantine plans and included infection probability, incubation period, interactions among birds, and quarantine region.</p> <p>Results</p> <p>We conducted sensitivity analysis for the different parameters in the model. Our study shows that the quarantine plan with well-chosen values of parameters is critical for minimize loss of poultry flocks in an AI outbreak. Specifically, the aggressive culling plan of infected poultry farms over 18.75 km radius range is unlikely to be effective, resulting in higher fractions of unnecessarily culled poultry flocks and the weak culling plan is also unlikely to be effective, resulting in higher fractions of infected poultry flocks.</p> <p>Conclusions</p> <p>Our results show that a prepared response with targeted quarantine protocols would have a high probability of containing the disease. The containment plan with an aggressive culling plan is not necessarily efficient, causing a higher fraction of unnecessarily culled poultry farms. Instead, it is necessary to balance culling with other important factors involved in AI spreading. Better estimations for the containment of AI spreading with this model offer the potential to reduce the loss of poultry and minimize economic impact on the poultry industry.</p

Killing of Targets by CD8+ T Cells in the Mouse Spleen Follows the Law of Mass Action

It has been difficult to correlate the quality of CD8 T cell responses with protection against viral infections. To investigate the relationship between efficacy and magnitude of T cell responses, we quantify the rate at which individual CD8 effector and memory T cells kill target cells in the mouse spleen. Using mathematical modeling, we analyze recent data on the loss of target cells pulsed with three different peptides from the mouse lymphocytic choriomeningitis virus (LCMV) in mouse spleens with varying numbers of epitope-specific CD8 T cells. We find that the killing of targets follows the law of mass-action, i.e., the death rate of individual target cells remains proportional to the frequency (or the total number) of specific CD8 T cells in the spleen despite the fact that effector cell densities and effector to target ratios vary about a 1000-fold. The killing rate of LCMV-specific CD8 T cells is largely independent of T cell specificity and differentiation stage. Our results thus allow one to calculate the critical T cell concentration at which growth of a virus with a given replication rate can be prevented from the start of infection by memory CD8 T cell response

Cure of Chronic Viral Infection and Virus-Induced Type 1 Diabetes by Neutralizing Antibodies

The use of neutralizing antibodies is one of the most successful methods to interfere with receptor–ligand interactions in vivo. In particular blockade of soluble inflammatory mediators or their corresponding cellular receptors was proven an effective way to regulate inflammation and/or prevent its negative consequences. However, one problem that comes along with an effective neutralization of inflammatory mediators is the general systemic immunomodulatory effect. It is, therefore, important to design a treatment regimen in a way to strike at the right place and at the right time in order to achieve maximal effects with minimal duration of immunosuppression or hyperactivation. In this review, we reflect on two examples of how short time administration of such neutralizing antibodies can block two distinct inflammatory consequences of viral infection. First, we review recent findings that blockade of IL-10/IL-10R interaction can resolve chronic viral infection and second, we reflect on how neutralization of the chemokine CXCL10 can abrogate virus-induced type 1 diabetes

IL-2 Mediates CD4+ T Cell Help in the Breakdown of Memory-Like CD8+ T Cell Tolerance under Lymphopenic Conditions

Background: Lymphopenia results in the proliferation and differentiation of naïve T cells into memory-like cells in the apparent absence of antigenic stimulation. This response, at least in part due to a greater availability of cytokines, is thought to promote anti-self responses. Although potentially autoreactive memory-like CD8 + T cells generated in a lymphopenic environment are subject to the mechanisms of peripheral tolerance, they can induce autoimmunity in the presence of antigen-specific memory-like CD4 + T helper cells. Methodology/Principal Findings: Here, we studied the mechanisms underlying CD4 help under lymphopenic conditions in transgenic mice expressing a model antigen in the beta cells of the pancreas. Surprisingly, we found that the self-reactivity mediated by the cooperation of memory-like CD8 + and CD4 + T cells was not abrogated by CD40L blockade. In contrast, treatment with anti-IL-2 antibodies inhibited the onset of autoimmunity. IL-2 neutralization prevented the CD4-mediated differentiation of memory-like CD8 + T cells into pathogenic effectors in response to self-antigen cross-presentation. Furthermore, in the absence of helper cells, induction of IL-2 signaling by an IL-2 immune complex was sufficient to promote memory-like CD8 + T cell self-reactivity. Conclusions/Significance: IL-2 mediates the cooperation of memory-like CD4 + and CD8 + T cells in the breakdown of crosstolerance, resulting in effector cytotoxic T lymphocyte differentiation and the induction of autoimmune disease

Genetic load and transgenic mitigating genes in transgenic Brassica rapa (field mustard) × Brassica napus (oilseed rape) hybrid populations

<p>Abstract</p> <p>Background</p> <p>One theoretical explanation for the relatively poor performance of <it>Brassica rapa </it>(weed) × <it>Brassica napus </it>(crop) transgenic hybrids suggests that hybridization imparts a negative genetic load. Consequently, in hybrids genetic load could overshadow any benefits of fitness enhancing transgenes and become the limiting factor in transgenic hybrid persistence. Two types of genetic load were analyzed in this study: random/linkage-derived genetic load, and directly incorporated genetic load using a transgenic mitigation (TM) strategy. In order to measure the effects of random genetic load, hybrid productivity (seed yield and biomass) was correlated with crop- and weed-specific AFLP genomic markers. This portion of the study was designed to answer whether or not weed × transgenic crop hybrids possessing more crop genes were less competitive than hybrids containing fewer crop genes. The effects of directly incorporated genetic load (TM) were analyzed through transgene persistence data. TM strategies are proposed to decrease transgene persistence if gene flow and subsequent transgene introgression to a wild host were to occur.</p> <p>Results</p> <p>In the absence of interspecific competition, transgenic weed × crop hybrids benefited from having more crop-specific alleles. There was a positive correlation between performance and number of <it>B. napus </it>crop-specific AFLP markers [seed yield vs. marker number (r = 0.54, P = 0.0003) and vegetative dry biomass vs. marker number (r = 0.44, P = 0.005)]. However under interspecific competition with wheat or more weed-like conditions (i.e. representing a situation where hybrid plants emerge as volunteer weeds in subsequent cropping systems), there was a positive correlation between the number of <it>B. rapa </it>weed-specific AFLP markers and seed yield (r = 0.70, P = 0.0001), although no such correlation was detected for vegetative biomass. When genetic load was directly incorporated into the hybrid genome, by inserting a fitness-mitigating dwarfing gene that that is beneficial for crops but deleterious for weeds (a transgene mitigation measure), there was a dramatic decrease in the number of transgenic hybrid progeny persisting in the population.</p> <p>Conclusion</p> <p>The effects of genetic load of crop and in some situations, weed alleles might be beneficial under certain environmental conditions. However, when genetic load was directly incorporated into transgenic events, e.g., using a TM construct, the number of transgenic hybrids and persistence in weedy genomic backgrounds was significantly decreased.</p

Molecular evolution of cyclin proteins in animals and fungi

<p>Abstract</p> <p>Background</p> <p>The passage through the cell cycle is controlled by complexes of cyclins, the regulatory units, with cyclin-dependent kinases, the catalytic units. It is also known that cyclins form several families, which differ considerably in primary structure from one eukaryotic organism to another. Despite these lines of evidence, the relationship between the evolution of cyclins and their function is an open issue. Here we present the results of our study on the molecular evolution of A-, B-, D-, E-type cyclin proteins in animals and fungi.</p> <p>Results</p> <p>We constructed phylogenetic trees for these proteins, their ancestral sequences and analyzed patterns of amino acid replacements. The analysis of infrequently fixed atypical amino acid replacements in cyclins evidenced that accelerated evolution proceeded predominantly during paralog duplication or after it in animals and fungi and that it was related to aromorphic changes in animals. It was shown also that evolutionary flexibility of cyclin function may be provided by consequential reorganization of regions on protein surface remote from CDK binding sites in animal and fungal cyclins and by functional differentiation of paralogous cyclins formed in animal evolution.</p> <p>Conclusions</p> <p>The results suggested that changes in the number and/or nature of cyclin-binding proteins may underlie the evolutionary role of the alterations in the molecular structure of cyclins and their involvement in diverse molecular-genetic events.</p

Transformation of Human Mesenchymal Cells and Skin Fibroblasts into Hematopoietic Cells

Patients with prolonged myelosuppression require frequent platelet and occasional granulocyte transfusions. Multi-donor transfusions induce alloimmunization, thereby increasing morbidity and mortality. Therefore, an autologous or HLA-matched allogeneic source of platelets and granulocytes is needed. To determine whether nonhematopoietic cells can be reprogrammed into hematopoietic cells, human mesenchymal stromal cells (MSCs) and skin fibroblasts were incubated with the demethylating agent 5-azacytidine (Aza) and the growth factors (GF) granulocyte-macrophage colony-stimulating factor and stem cell factor. This treatment transformed MSCs to round, non-adherent cells expressing T-, B-, myeloid-, or stem/progenitor-cell markers. The transformed cells engrafted as hematopoietic cells in bone marrow of immunodeficient mice. DNA methylation and mRNA array analysis suggested that Aza and GF treatment demethylated and activated HOXB genes. Indeed, transfection of MSCs or skin fibroblasts with HOXB4, HOXB5, and HOXB2 genes transformed them into hematopoietic cells. Further studies are needed to determine whether transformed MSCs or skin fibroblasts are suitable for therapy