Differential Effect of IL-27 on Developing versus Committed Th17 Cells

IIL-27 counters the effect of TGF-beta+IL-6 on naive CD4(+) T cells, resulting in near complete inhibition of de novo Th17 development. In contrast, little is known about the effect of IL-27 on already differentiated Th17 cells. A better understanding of how IL-27 regulates these cells is needed to evaluate the therapeutic potential of IL-27 in Th17 cells-associated diseases. In this study, we show that IL-27 had surprisingly little effect on committed Th17 cells, despite its expression of a functional IL-27R. Contrary to de novo differentiation of Th17 cells, IL-27 did not suppress expression of retinoid-related orphan receptor (ROR)gammat or RORalpha in committed Th17 cells. Consistent with this finding, the frequency of committed Th17 cells and their cytokine secretion remained unaffected by IL-27. Both memory Th17 cells (CD4(+)CD25(-)CD62L(low)) that developed in vivo and encephalitogenic Th17 cells infiltrating the CNS of mice developing experimental autoimmune encephalomyelitis produced similar amounts of IL-17A when reactivated with IL-23 in the absence and presence of exogenous IL-27. Finally, IL-27 failed to suppress encephalitogenicity of Th17 cells in an adoptive transfer of experimental autoimmune encephalomyelitis. Analysis ex vivo of transferred Th17 cells in the spleen and CNS of recipient mice showed that cells retained similar phenotype irrespective of whether cells were treated or not with IL-27. Our data demonstrate that in contrast to inhibition of de novo differentiation of Th17 cells, IL-27 has little or no effect on committed Th17 cells. These findings indicate that therapeutic applications of IL-27 might have a limited efficacy in inflammatory conditions where aggressive Th17 responses have already developed.

Cell-to-Cell Interactions and Signals Involved in the Reconstitution of Peripheral CD8(+) T-CM and T-EM Cell Pools

We here describe novel aspects of CD8(+) and CD4(+) T cell subset interactions that may be clinically relevant and provide new tools for regulating the reconstitution of the peripheral CD8(+) T cell pools in immune-deficient states. We show that the reconstitution capacity of transferred isolated naive CD8(+) T cells and their differentiation of effector functions is limited, but both dramatically increase upon the co-transfer of CD4(+) T cells. This helper effect is complex and determined by multiple factors. It was directly correlated to the number of helper cells, required the continuous presence of the CD4(+) T cells, dependent on host antigen-presenting cells (APCs) expressing CD40 and on the formation of CD4/CD8/APC cell clusters. By comparing the recovery of (CD44(+)CD62L(high)) T-CM and (CD44(+)CD62L(low)) T-EM CD8(+) T cells, we found that the accumulation of TCM and TEM subsets is differentially regulated. T-CM-cell accumulation depended mainly on type I interferons, interleukin (IL)-6, and IL-15, but was independent of CD4(+) T-cell help. In contrast, TEM-cell expansion was mainly determined by CD4(+) T-cell help and dependent on the expression of IL-2R beta by CD8 cells, on IL-2 produced by CD4(+) T-cells, on IL-15 and to a minor extent on IL-6.

Dispelling the Myth of the Naive Investor during the British Railway Mania, 1845–46

Anecdotal evidence from the British Railway Mania and other historical financial bubbles suggests that many investors during such episodes are naive, thus contributing to the asset price boom. Using extensive investor records, we find that very few investors during the Railway Mania can be categorized as such. Although some interpretations of the Mania suggest that naive investors were expropriated by railway insiders, our evidence is inconsistent with this view as railway insiders contributed substantial amounts of capital, and their investments performed no better than those made by other experienced investors.

Novel genetic susceptibility loci for diabetic end-stage renal disease identified through robust naive Bayes classification

Aims/hypothesis: Diabetic nephropathy is a major diabetic complication, and diabetes is the leading cause of end-stage renal disease (ESRD). Family studies suggest a hereditary component for diabetic nephropathy. However, only a few genes have been associated with diabetic nephropathy or ESRD in diabetic patients. Our aim was to detect novel genetic variants associated with diabetic nephropathy and ESRD. Methods: We exploited a novel algorithm, ‘Bag of Naive Bayes’, whose marker selection strategy is complementary to that of conventional genome-wide association models based on univariate association tests. The analysis was performed on a genome-wide association study of 3,464 patients with type 1 diabetes from the Finnish Diabetic Nephropathy (FinnDiane) Study and subsequently replicated with 4,263 type 1 diabetes patients from the Steno Diabetes Centre, the All Ireland-Warren 3-Genetics of Kidneys in Diabetes UK collection (UK–Republic of Ireland) and the Genetics of Kidneys in Diabetes US Study (GoKinD US). Results: Five genetic loci (WNT4/ZBTB40-rs12137135, RGMA/MCTP2-rs17709344, MAPRE1P2-rs1670754, SEMA6D/SLC24A5-rs12917114 and SIK1-rs2838302) were associated with ESRD in the FinnDiane study. An association between ESRD and rs17709344, tagging the previously identified rs12437854 and located between the RGMA and MCTP2 genes, was replicated in independent case–control cohorts. rs12917114 near SEMA6D was associated with ESRD in the replication cohorts under the genotypic model (p < 0.05), and rs12137135 upstream of WNT4 was associated with ESRD in Steno. Conclusions/interpretation: This study supports the previously identified findings on the RGMA/MCTP2 region and suggests novel susceptibility loci for ESRD. This highlights the importance of applying complementary statistical methods to detect novel genetic variants in diabetic nephropathy and, in general, in complex diseases.

Extended Tree Augmented Naive Classifier

This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier where the structure learning step is performed without requiring features to be connected to the class. Based on a modification of Edmonds’ algorithm, our structure learning procedure explores a superset of the structures that are considered by TAN, yet achieves global optimality of the learning score function in a very efficient way (quadratic in the number of features, the same complexity as learning TANs). A range of experiments show that we obtain models with better accuracy than TAN and comparable to the accuracy of the state-of-the-art classifier averaged one-dependence estimator.

Averaged Extended Tree Augmented Naive Classifier

This work presents a new general purpose classifier named Averaged Extended Tree Augmented Naive Bayes (AETAN), which is based on combining the advantageous characteristics of Extended Tree Augmented Naive Bayes (ETAN) and Averaged One-Dependence Estimator (AODE) classifiers. We describe the main properties of the approach and algorithms for learning it, along with an analysis of its computational time complexity. Empirical results with numerous data sets indicate that the new approach is superior to ETAN and AODE in terms of both zero-one classification accuracy and log loss. It also compares favourably against weighted AODE and hidden Naive Bayes. The learning phase of the new approach is slower than that of its competitors, while the time complexity for the testing phase is similar. Such characteristics suggest that the new classifier is ideal in scenarios where online learning is not required.

Learning Extended Tree Augmented Naive Structures

This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier where the structure learning step is performed without requiring features to be connected to the class. Based on a modification of Edmonds' algorithm, our structure learning procedure explores a superset of the structures that are considered by TAN, yet achieves global optimality of the learning score function in a very efficient way (quadratic in the number of features, the same complexity as learning TANs). We enhance our procedure with a new score function that only takes into account arcs that are relevant to predict the class, as well as an optimization over the equivalent sample size during learning. These ideas may be useful for structure learning of Bayesian networks in general. A range of experiments shows that we obtain models with better prediction accuracy than naive Bayes and TAN, and comparable to the accuracy of the state-of-the-art classifier averaged one-dependence estimator (AODE). We release our implementation of ETAN so that it can be easily installed and run within Weka.

Habitat-specific adaptation of immune responses of stickleback (Gasterosteus aculeatus) lake and river ecotypes

Freshwater populations of three-spined sticklebacks (Gasterosteus aculeatus) in northern Germany are found as distinct lake and river ecotypes. Adaptation to habitat-specific parasites might influence immune capabilities of stickleback ecotypes. Here, naive laboratory-bred sticklebacks from lake and river populations were exposed reciprocally to parasite environments in a lake and a river habitat. Sticklebacks exposed to lake conditions were infected with higher numbers of parasite species when compared with the river. River sticklebacks in the lake had higher parasite loads than lake sticklebacks in the same habitat. Respiratory burst, granulocyte counts and lymphocyte proliferation of head kidney leucocytes were increased in river sticklebacks exposed to lake when compared with river conditions. Although river sticklebacks exposed to lake conditions showed elevated activation of their immune system, parasites could not be diminished as effectively as by lake sticklebacks in their native habitat. River sticklebacks seem to have reduced their immune-competence potential due to lower parasite diversity in rivers

Blood-derived dermal langerin+ dendritic cells survey the skin in the steady state.

Langerin is a C-type lectin receptor that recognizes glycosylated patterns on pathogens. Langerin is used to identify human and mouse epidermal Langerhans cells (LCs), as well as migratory LCs in the dermis and the skin draining lymph nodes (DLNs). Using a mouse model that allows conditional ablation of langerin(+) cells in vivo, together with congenic bone marrow chimeras and parabiotic mice as tools to differentiate LC- and blood-derived dendritic cells (DCs), we have revisited the origin of langerin(+) DCs in the skin DLNs. Our results show that in contrast to the current view, langerin(+)CD8(-) DCs in the skin DLNs do not derive exclusively from migratory LCs, but also include blood-borne langerin(+) DCs that transit through the dermis before reaching the DLN. The recruitment of circulating langerin(+) DCs to the skin is dependent on endothelial selectins and CCR2, whereas their recruitment to the skin DLNs requires CCR7 and is independent of CD62L. We also show that circulating langerin(+) DCs patrol the dermis in the steady state and migrate to the skin DLNs charged with skin antigens. We propose that this is an important and previously unappreciated element of immunosurveillance that needs to be taken into account in the design of novel vaccine strategies.

Antigen-specific T-T interactions regulate CD4 T-cell expansion.

The regulation of CD4 T cell numbers during an immune response should take account of the amount of antigen (Ag), the initial frequency of Ag-specific T cells, the mix of naive versus experienced cells, and (ideally) the diversity of the repertoire. Here we describe a novel mechanism of T cell regulation that potentially deals with all of these parameters. We found that CD4 T cells establish a negative feedback loop by capturing their cognate MHC/peptide complexes from Ag-presenting cells and presenting them to Ag-experienced CD4 T cells, thereby inhibiting their recruitment into the response while allowing recruitment of naive T cells. The inhibition is Ag specific, begins at day 2 (long before Ag disappearance), and cannot be overcome by providing new Ag-loaded dendritic cells. In this way CD4 T cell proliferation is regulated in a functional relationship to the amount of Ag, while allowing naive T cells to generate repertoire variety.

Spatial attentional bias as a marker of genetic risk, symptom severity, and stimulant response in ADHD

Attention-deficit hyperactivity disorder (ADHD) is a heritable childhood onset disorder that is marked by variability at multiple levels including clinical presentation, cognitive profile, and response to stimulant medications. It has been suggested that this variability may reflect etiological differences, particularly, at the level of underlying genetics. This study examined whether an attentional phenotype-spatial attentional bias could serve as a marker of symptom severity, genetic risk, and stimulant response in ADHD. A total of 96 children and adolescents with ADHD were assessed on the Landmark Task, which is a sensitive measure of spatial attentional bias. All children were genotyped for polymorphisms (30 untranslated (UTR) and intron 8 variable number of tandem repeats (VNTRs)) of the dopamine transporter gene (DAT1). Spatial attentional bias correlated with ADHD symptom levels and varied according to DAT1 genotype. Children who were homozygous for the 10-repeat allele of the DAT1 30-UTR VNTR displayed a rightward attentional bias and had higher symptom levels compared to those with the low-risk genotype. A total of 26 of these children who were medication naive performed the Landmark Task at baseline and then again after 6 weeks of stimulant medication. Left-sided inattention (rightward bias) at baseline was associated with an enhanced response to stimulants at 6 weeks. Moreover, changes in spatial bias with stimulant medications, varied as a function of DAT1 genotype. This study suggests an attentional phenotype that relates to symptom severity and genetic risk for ADHD, and may have utility in predicting stimulant response in ADHD.