Host Iron Binding Proteins Acting as Niche Indicators for Neisseria meningitidis

Neisseria meningitidis requires iron, and in the absence of iron alters its gene expression to increase iron acquisition and to make the best use of the iron it has. During different stages of colonization and infection available iron sources differ, particularly the host iron-binding proteins haemoglobin, transferrin, and lactoferrin. This study compared the transcriptional responses of N. meningitidis, when grown in the presence of these iron donors and ferric iron, using microarrays

Assessment of nerve involvement in the lumbar spine: agreement between magnetic resonance imaging, physical examination and pain drawing findings

<p>Abstract</p> <p>Background</p> <p>Detection of nerve involvement originating in the spine is a primary concern in the assessment of spine symptoms. Magnetic resonance imaging (MRI) has become the diagnostic method of choice for this detection. However, the agreement between MRI and other diagnostic methods for detecting nerve involvement has not been fully evaluated. The aim of this diagnostic study was to evaluate the agreement between nerve involvement visible in MRI and findings of nerve involvement detected in a structured physical examination and a simplified pain drawing.</p> <p>Methods</p> <p>Sixty-one consecutive patients referred for MRI of the lumbar spine were - without knowledge of MRI findings - assessed for nerve involvement with a simplified pain drawing and a structured physical examination. Agreement between findings was calculated as overall agreement, the p value for McNemar's exact test, specificity, sensitivity, and positive and negative predictive values.</p> <p>Results</p> <p>MRI-visible nerve involvement was significantly less common than, and showed weak agreement with, physical examination and pain drawing findings of nerve involvement in corresponding body segments. In spine segment L4-5, where most findings of nerve involvement were detected, the mean sensitivity of MRI-visible nerve involvement to a positive neurological test in the physical examination ranged from 16-37%. The mean specificity of MRI-visible nerve involvement in the same segment ranged from 61-77%. Positive and negative predictive values of MRI-visible nerve involvement in segment L4-5 ranged from 22-78% and 28-56% respectively.</p> <p>Conclusion</p> <p>In patients with long-standing nerve root symptoms referred for lumbar MRI, MRI-visible nerve involvement significantly underestimates the presence of nerve involvement detected by a physical examination and a pain drawing. A structured physical examination and a simplified pain drawing may reveal that many patients with "MRI-invisible" lumbar symptoms need treatment aimed at nerve involvement. Factors other than present MRI-visible nerve involvement may be responsible for findings of nerve involvement in the physical examination and the pain drawing.</p

Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

<p>Abstract</p> <p>Background</p> <p>Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes.</p> <p>Methods</p> <p>Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR) to neoadjuvant chemotherapy were also built using this approach.</p> <p>Results</p> <p>We identified statistically significant prognostic models for relapse-free survival (RFS) at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR) predictions for the entire population.</p> <p>Conclusions</p> <p>Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA copy number changes, will be needed to build robust prognostic models for ER-negative breast cancer patients. This combined clinical and genomics model approach can also be used to build predictors of therapy responsiveness, and could ultimately be applied to other tumor types.</p

Estimating economies of scale and scope with flexible technology

The final publication is available at Springer via http://dx.doi.org/10.1007/s11123-016-0467-1Economies of scope are typically modelled and estimated using a cost function that is common to all firms in an industry irrespective of their type, e.g. whether they specialize in a single output or produce multiple outputs. Instead, we estimate a flexible technology model that allows for type-specific technologies and show how it can be estimated using linear parametric forms including the translog. A common technology remains a special case of our model and is testable econometrically. Our sample, of publicly owned US electric utilities, does not support a common technology for integrated and specialized firms. Our empirical results therefore suggest that assuming a common technology might bias estimates of economies of scale and scope. Thus, how we model the production technology clearly influences the policy conclusions we draw from its characteristics

Transcriptome Analysis of Neisseria meningitidis in Human Whole Blood and Mutagenesis Studies Identify Virulence Factors Involved in Blood Survival

During infection Neisseria meningitidis (Nm) encounters multiple environments within the host, which makes rapid adaptation a crucial factor for meningococcal survival. Despite the importance of invasion into the bloodstream in the meningococcal disease process, little is known about how Nm adapts to permit survival and growth in blood. To address this, we performed a time-course transcriptome analysis using an ex vivo model of human whole blood infection. We observed that Nm alters the expression of ≈30% of ORFs of the genome and major dynamic changes were observed in the expression of transcriptional regulators, transport and binding proteins, energy metabolism, and surface-exposed virulence factors. In particular, we found that the gene encoding the regulator Fur, as well as all genes encoding iron uptake systems, were significantly up-regulated. Analysis of regulated genes encoding for surface-exposed proteins involved in Nm pathogenesis allowed us to better understand mechanisms used to circumvent host defenses. During blood infection, Nm activates genes encoding for the factor H binding proteins, fHbp and NspA, genes encoding for detoxifying enzymes such as SodC, Kat and AniA, as well as several less characterized surface-exposed proteins that might have a role in blood survival. Through mutagenesis studies of a subset of up-regulated genes we were able to identify new proteins important for survival in human blood and also to identify additional roles of previously known virulence factors in aiding survival in blood. Nm mutant strains lacking the genes encoding the hypothetical protein NMB1483 and the surface-exposed proteins NalP, Mip and NspA, the Fur regulator, the transferrin binding protein TbpB, and the L-lactate permease LctP were sensitive to killing by human blood. This increased knowledge of how Nm responds to adaptation in blood could also be helpful to develop diagnostic and therapeutic strategies to control the devastating disease cause by this microorganism