Differential expression analysis with global network adjustment

<p>Background: Large-scale chromosomal deletions or other non-specific perturbations of the transcriptome can alter the expression of hundreds or thousands of genes, and it is of biological interest to understand which genes are most profoundly affected. We present a method for predicting a gene’s expression as a function of other genes thereby accounting for the effect of transcriptional regulation that confounds the identification of genes differentially expressed relative to a regulatory network. The challenge in constructing such models is that the number of possible regulator transcripts within a global network is on the order of thousands, and the number of biological samples is typically on the order of 10. Nevertheless, there are large gene expression databases that can be used to construct networks that could be helpful in modeling transcriptional regulation in smaller experiments.</p> <p>Results: We demonstrate a type of penalized regression model that can be estimated from large gene expression databases, and then applied to smaller experiments. The ridge parameter is selected by minimizing the cross-validation error of the predictions in the independent out-sample. This tends to increase the model stability and leads to a much greater degree of parameter shrinkage, but the resulting biased estimation is mitigated by a second round of regression. Nevertheless, the proposed computationally efficient “over-shrinkage” method outperforms previously used LASSO-based techniques. In two independent datasets, we find that the median proportion of explained variability in expression is approximately 25%, and this results in a substantial increase in the signal-to-noise ratio allowing more powerful inferences on differential gene expression leading to biologically intuitive findings. We also show that a large proportion of gene dependencies are conditional on the biological state, which would be impossible with standard differential expression methods.</p> <p>Conclusions: By adjusting for the effects of the global network on individual genes, both the sensitivity and reliability of differential expression measures are greatly improved.</p&gt

Diagnostic accuracy of existing methods for identifying diabetic foot ulcers from inpatient and outpatient datasets

<p>Abstract</p> <p>Background</p> <p>As the number of persons with diabetes is projected to double in the next 25 years in the US, an accurate method of identifying diabetic foot ulcers in population-based data sources are ever more important for disease surveillance and public health purposes. The objectives of this study are to evaluate the accuracy of existing methods and to propose a new method.</p> <p>Methods</p> <p>Four existing methods were used to identify all patients diagnosed with a foot ulcer in a Department of Veterans Affairs (VA) hospital from the inpatient and outpatient datasets for 2003. Their electronic medical records were reviewed to verify whether the medical records positively indicate presence of a diabetic foot ulcer in diagnoses, medical assessments, or consults. For each method, five measures of accuracy and agreement were evaluated using data from medical records as the gold standard.</p> <p>Results</p> <p>Our medical record reviews show that all methods had sensitivity > 92% but their specificity varied substantially between 74% and 91%. A method used in Harrington et al. (2004) was the most accurate with 94% sensitivity and 91% specificity and produced an annual prevalence of 3.3% among VA users with diabetes nationwide. A new and simpler method consisting of two codes (707.1× and 707.9) shows an equally good accuracy with 93% sensitivity and 91% specificity and 3.1% prevalence.</p> <p>Conclusions</p> <p>Our results indicate that the Harrington and New methods are highly comparable and accurate. We recommend the Harrington method for its accuracy and the New method for its simplicity and comparable accuracy.</p

Physics of Neutron Star Crusts

The physics of neutron star crusts is vast, involving many different research fields, from nuclear and condensed matter physics to general relativity. This review summarizes the progress, which has been achieved over the last few years, in modeling neutron star crusts, both at the microscopic and macroscopic levels. The confrontation of these theoretical models with observations is also briefly discussed.Comment: 182 pages, published version available at <http://www.livingreviews.org/lrr-2008-10

The aldehyde dehydrogenase AldA contributes to the hypochlorite defense and is redox-controlled by protein S-bacillithiolation in Staphylococcus aureus

Staphylococcus aureus produces bacillithiol (BSH) as major low molecular weight (LMW) thiol which functions in thiol-protection and redox-regulation by protein S-bacillithiolation under hypochlorite stress. The aldehyde dehydrogenase AldA was identified as S-bacillithiolated at its active site Cys279 under NaOCl stress in S. aureus. Here, we have studied the expression, function, redox regulation and structural changes of AldA of S. aureus. Transcription of aldA was previously shown to be regulated by the alternative sigma factor SigmaB. Northern blot analysis revealed SigmaB-independent induction of aldA transcription under formaldehyde, methylglyoxal, diamide and NaOCl stress. Deletion of aldA resulted in a NaOCl-sensitive phenotype in survival assays, suggesting an important role of AldA in the NaOCl stress defense. Purified AldA showed broad substrate specificity for oxidation of several aldehydes, including formaldehyde, methylglyoxal, acetaldehyde and glycol aldehyde. Thus, AldA could be involved in detoxification of aldehyde substrates that are elevated under NaOCl stress. Kinetic activity assays revealed that AldA is irreversibly inhibited under H2O2 treatment in vitro due to overoxidation of Cys279 in the absence of BSH. Pre-treatment of AldA with BSH prior to H2O2 exposure resulted in reversible AldA inactivation due to S-bacillithiolation as revealed by activity assays and BSH-specific Western blot analysis. Using molecular docking and molecular dynamic simulation, we further show that BSH occupies two different positions in the AldA active site depending on the AldA activation state. In conclusion, we show here that AldA is an important target for S-bacillithiolation in S. aureus that is up-regulated under NaOCl stress and functions in protection under hypochlorite stress

Immunological network signatures of cancer progression and survival

<p>Abstract</p> <p>Background</p> <p>The immune contribution to cancer progression is complex and difficult to characterize. For example in tumors, immune gene expression is detected from the combination of normal, tumor and immune cells in the tumor microenvironment. Profiling the immune component of tumors may facilitate the characterization of the poorly understood roles immunity plays in cancer progression. However, the current approaches to analyze the immune component of a tumor rely on incomplete identification of immune factors.</p> <p>Methods</p> <p>To facilitate a more comprehensive approach, we created a ranked immunological relevance score for all human genes, developed using a novel strategy that combines text mining and information theory. We used this score to assign an immunological grade to gene expression profiles, and thereby quantify the immunological component of tumors. This immunological relevance score was benchmarked against existing manually curated immune resources as well as high-throughput studies. To further characterize immunological relevance for genes, the relevance score was charted against both the human interactome and cancer information, forming an expanded interactome landscape of tumor immunity. We applied this approach to expression profiles in melanomas, thus identifying and grading their immunological components, followed by identification of their associated protein interactions.</p> <p>Results</p> <p>The power of this strategy was demonstrated by the observation of early activation of the adaptive immune response and the diversity of the immune component during melanoma progression. Furthermore, the genome-wide immunological relevance score classified melanoma patient groups, whose immunological grade correlated with clinical features, such as immune phenotypes and survival.</p> <p>Conclusions</p> <p>The assignment of a ranked immunological relevance score to all human genes extends the content of existing immune gene resources and enriches our understanding of immune involvement in complex biological networks. The application of this approach to tumor immunity represents an automated systems strategy that quantifies the immunological component in complex disease. In so doing, it stratifies patients according to their immune profiles, which may lead to effective computational prognostic and clinical guides.</p

Early Life Events Carry Over to Influence Pre-Migratory Condition in a Free-Living Songbird

Conditions experienced during development can have long-term consequences for individual success. In migratory songbirds, the proximate mechanisms linking early life events and survival are not well understood because tracking individuals across stages of the annual cycle can be extremely challenging. In this paper, we first use a 13 year dataset to demonstrate a positive relationship between 1st year survival and nestling mass in migratory Savannah sparrows (Passerculus sandwichensis). We also use a brood manipulation experiment to show that nestlings from smaller broods have higher mass in the nest relative to individuals from larger broods. Having established these relationships, we then use three years of field data involving multiple captures of individuals throughout the pre-migratory period and a multi-level path model to examine the hypothesis that conditions during development limit survival during migration by affecting an individual's ability to accumulate sufficient lean tissue and fat mass prior to migration. We found a positive relationship between fat mass during the pre-migratory period (Sept–Oct) and nestling mass and a negative indirect relationship between pre-migratory fat mass and fledging date. Our results provide the first evidence that conditions during development limit survival during migration through their effect on fat stores. These results are particularly important given recent evidence showing that body condition of songbirds at fledging is affected by climate change and anthropogenic changes to landscape structure