Re-Annotation Is an Essential Step in Systems Biology Modeling of Functional Genomics Data

One motivation of systems biology research is to understand gene functions and interactions from functional genomics data such as that derived from microarrays. Up-to-date structural and functional annotations of genes are an essential foundation of systems biology modeling. We propose that the first essential step in any systems biology modeling of functional genomics data, especially for species with recently sequenced genomes, is gene structural and functional re-annotation. To demonstrate the impact of such re-annotation, we structurally and functionally re-annotated a microarray developed, and previously used, as a tool for disease research. We quantified the impact of this re-annotation on the array based on the total numbers of structural- and functional-annotations, the Gene Annotation Quality (GAQ) score, and canonical pathway coverage. We next quantified the impact of re-annotation on systems biology modeling using a previously published experiment that used this microarray. We show that re-annotation improves the quantity and quality of structural- and functional-annotations, allows a more comprehensive Gene Ontology based modeling, and improves pathway coverage for both the whole array and a differentially expressed mRNA subset. Our results also demonstrate that re-annotation can result in a different knowledge outcome derived from previous published research findings. We propose that, because of this, re-annotation should be considered to be an essential first step for deriving value from functional genomics data

The CIPRUS study, a nurse-led psychological treatment for patients with undifferentiated somatoform disorder in primary care: study protocol for a randomised controlled trial

Background: Up to a third of patients presenting medically unexplained physical symptoms in primary care may have a somatoform disorder, of which undifferentiated somatoform disorder (USD) is the most common type. Psychological interventions can reduce symptoms associated with USD and improve functioning. Previous research has either been conducted in secondary care or interventions have been provided by general practitioners (GPs) or psychologists in primary care. As efficiency and cost-effectiveness are imperative in primary care, it is important to investigate whether nurse-led interventions are effective as well. The aim of this study is to examine the effectiveness and cost-effectiveness of a short cognitive behavioural therapy (CBT)-based treatment for patients with USD provided by mental health nurse practitioners (MHNPs), compared to usual care. Methods: In a cluster randomised controlled trial, 212 adult patients with USD will be assigned to the intervention or care as usual. The intervention group will be offered a short, individual CBT-based treatment by the MHNP in addition to usual GP care. The main goal of the intervention is that patients become less impaired by their physical symptoms and cope with symptoms in a more effective way. In six sessions patients will receive problem-solving treatment. The primary outcome is improvement in physical functioning, measured by the physical component summary score of the RAND-36. Secondary outcomes include health-related quality of life measured by the separate subscales of the RAND-36, somatization (PHQ-15) and symptoms of depression and anxiety (HADS). Problem-solving skills, health anxiety, illness perceptions, coping, mastery and working alliance will be assessed as potential mediators. Assessments will be done at 0, 2, 4, 8 and 12 months. An economic evaluation will be conducted from a societal perspective with quality of life as the primary outcome measure assessed by the EQ-5D-5L. Health care, patient and lost productivity costs will be assessed with the Tic-P. Discussion: We expect that the intervention will improve physical functioning and is cost-effective compared to usual care. If so, more patients might successfully be treated in general practice, decreasing the number of referrals to specialist care. Trial registration: Dutch Trial Registry, identifier: NTR4686, Registered on 14 July 2014. © 2017 The Author(s)

Genomic and functional analyses of mycobacterium tuberculosis strains implicate ald in D-cycloserine resistance.

CAPRISA, 2016.Abstract available in PDF file

Comparison of organic and integrated nutrient management strategies for reducing soil N2O emissions

To prevent nutrient limitations to crop growth, nitrogen is often applied in agricultural systems in the form of organic inputs (e.g., crop residues, manure, compost, etc.) or inorganic fertilizer. Inorganic nitrogen fertilizer has large environmental and economic costs, particularly for low-input smallholder farming systems. The concept of combining organic, inorganic, and biological nutrient sources through Integrated Nutrient Management (INM) is increasingly promoted as a means of improving nutrient use efficiency by matching soil nutrient availability with crop demand. While the majority of previous research on INM has focused on soil quality and yield, potential climate change impacts have rarely been assessed. In particular, it remains unclear whether INM increases or decreases soil nitrous oxide (N2O) emissions compared to organic nitrogen inputs, which may represent an overlooked environmental tradeoff. The objectives of this review were to (i) summarize the mechanisms influencingN2O emissions in response to organic and inorganic nitrogen (N) fertilizer sources, (ii) synthesize findings from the limited number of field experiments that have directly compared N2O emissions for organic N inputs vs. INM treatments, (iii) develop a hypothesis for conditions under which INM reduces N2O emissions and (iv) identify key knowledge gaps to address in future research. In general, INM treatments having low carbon to nitrogen ratio C:N (<8) tended to reduce emissions compared to organic amendments alone, while INM treatments with higher C:N resulted in no change or increased N2O emissions

Occupancy and fractal dimension analyses of the spatial distribution of cytotoxic (CD8+) T cells infiltrating the tumor microenvironment in triple negative breast cancer

Favorable outcomes have been associated with high densities of tumor infiltrating lymphocytes (TILs) such as cytotoxic (CD8+) T cells. However, the clinical signifi- cance of the spatial distribution of TILs is less well understood. We have developed novel statistical techniques to characterize the spatial distribution of TILs at various length scales. These include a box counting method that we call “occupancy” and novel applications of fractal dimensions. We apply these techniques to the spatial distribution of CD8+ T cells in the tumor microenvironment of tissue resected from 35 triple negative breast cancer patients. We find that there is a distinct difference in the spatial distribution of CD8+ T cells between good clinical outcome (no recurrence within at least 5 years of diagnosis) and poor clinical outcome (recurrence within 3 years of diagnosis). The statistical significance of the difference between good and poor outcome in the occupancy, fractal dimension (FD), and FD difference of CD8+ T cells is comparable to that of the CD8+ T cell density. Even when we randomly exclude some of the cells so that the images have the same cell density, we still find that the fractal dimension at short length scales is correlated with cancer recurrence, implying that the actual spatial distribution of CD8+ cells, and not just the CD8+ cell density, is associated with clinical outcome. The occupancy and FD difference indicate that the CD8+ T cells are more spatially dispersed in good outcome and more aggregated in poor outcome. We discuss possible interpretations