The battle against immunopathology: infectious tolerance mediated by regulatory T cells

Infectious tolerance is a process whereby one regulatory lymphoid population confers suppressive capacity on another. Diverse immune responses are induced following infection or inflammatory insult that can protect the host, or potentially cause damage if not properly controlled. Thus, the process of infectious tolerance may be critical in vivo for exerting effective immune control and maintaining immune homeostasis by generating specialized regulatory sub-populations with distinct mechanistic capabilities. Foxp3(+) regulatory T cells (T(regs)) are a central mediator of infectious tolerance through their ability to convert conventional T cells into induced regulatory T cells (iT(regs)) directly by secretion of the suppressive cytokines TGF-β, IL-10, or IL-35, or indirectly via dendritic cells. In this review, we will discuss the mechanisms and cell populations that mediate and contribute to infectious tolerance, with a focus on the intestinal environment, where tolerance induction to foreign material is critical.     

Forecast Evaluation of Nonlinear Models: The Case of Long‐Span Real Exchange Rates

This paper deals with the nonlinear modeling and forecasting of the dollar–sterling and franc–sterling real exchange rates using long spans of data. Our contribution is threefold. First, we provide significant evidence of smooth transition dynamics in the series by employing a battery of recently developed in‐sample statistical tests. Second, we investigate the small‐sample properties of several evaluation measures for comparing recursive forecasts when one of the competing models is nonlinear. Finally, we run a forecasting race for the post‐Bretton Woods era between the nonlinear real exchange rate model, the random walk, and the linear autoregressive model. The nonlinear model outperforms all rival models in the dollar–sterling case but cannot beat the linear autoregressive in the franc–sterling. Copyright © 2011 John Wiley & Sons, Ltd.     

Are Analysts' Loss Functions Asymmetric?

Despite displaying a statistically significant optimism bias, analysts' earnings forecasts are an important input to investors’ valuation models. Understanding the possible reasons for any bias is important if information is to be extracted from earnings forecasts and used optimally by investors. Extant research into the shape of analysts' loss functions explains optimism bias as resulting from analysts minimizing the mean absolute forecast error under symmetric, linear loss functions. When the distribution of earnings outcomes is skewed, optimalforecasts can appear biased. In contrast, research into analysts' economic incentives suggests that positive and negative earnings forecast errors made by analysts are not penalized or rewarded symmetrically, suggesting that asymmetric loss functions are an appropriate characterization. To reconcile these findings, we exploit results from economic theory relating to the Linex loss function to discriminate between the symmetric linear loss and the asymmetric loss explanations of analyst forecast bias. Under asymmetric loss functions optimal forecasts will appear biased even if earnings outcomes are symmetric. Our empirical results support the asymmetric loss function explanation. Further analysis also reveals that forecast bias varies systematically across firm characteristics that capture systematic variation in the earnings forecast error distribution. Copyright © 2011 John Wiley & Sons, Ltd.     

A Kuhnian defence of inference to the best explanation

According to inference to the best explanation (IBE), scientists infer the loveliest of competing hypotheses, ‘loveliness’ being explanatory virtue. This generates two key objections: that loveliness is too subjective to guide inference, and that it is no guide to truth. I defend IBE using Thomas Kuhn’s notion of exemplars: the scientific theories, or applications thereof, that define Kuhnian normal science and facilitate puzzle-solving. I claim that scientists infer the explanatory puzzle-solution that best meets the standard set by the relevant exemplar of loveliness. Exemplars are the subject of consensus, eliminating subjectivity; divorced from Kuhnian relativism, they give loveliness the context-sensitivity required to be truth-tropic. The resulting account, ‘Kuhnian IBE’, is independently plausible and offers a partial rapprochement between IBE and Kuhn’s account of science.     

Whole-genome sequence of Schistosoma haematobium

Schistosomiasis is a neglected tropical disease caused by blood flukes (genus Schistosoma; schistosomes) and affecting 200 million people worldwide. No vaccines are available, and treatment relies on one drug, praziquantel. Schistosoma haematobium has come into the spotlight as a major cause of urogenital disease, as an agent linked to bladder cancer and as a predisposing factor for HIV/AIDS. The parasite is transmitted to humans from freshwater snails. Worms dwell in blood vessels and release eggs that become embedded in the bladder wall to elicit chronic immune-mediated disease and induce squamous cell carcinoma. Here we sequenced the 385-Mb genome of S. haematobium using Illumina-based technology at 74-fold coverage and compared it to sequences from related parasites. We included genome annotation based on function, gene ontology, networking and pathway mapping. This genome now provides an unprecedented resource for many fundamental research areas and shows great promise for the design of new disease interventions.     

Common variants on 8p12 and 1q24.2 confer risk of schizophrenia

Schizophrenia is a severe mental disorder affecting ～1% of the world population, with heritability of up to 80%. To identify new common genetic risk factors, we performed a genome-wide association study (GWAS) in the Han Chinese population. The discovery sample set consisted of 3,750 individuals with schizophrenia and 6,468 healthy controls (1,578 cases and 1,592 controls from northern Han Chinese, 1,238 cases and 2,856 controls from central Han Chinese, and 934 cases and 2,020 controls from the southern Han Chinese). We further analyzed the strongest association signals in an additional independent cohort of 4,383 cases and 4,539 controls from the Han Chinese population. Meta-analysis identified common SNPs that associated with schizophrenia with genome-wide significance on 8p12 (rs16887244, P = 1.27 × 10(-10)) and 1q24.2 (rs10489202, P = 9.50 × 10(-9)). Our findings provide new insights into the pathogenesis of schizophrenia.     

Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease

More than 1,000 susceptibility loci have been identified through genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings have not yet been defined. Here we used pooled next-generation sequencing to study 56 genes from regions associated with Crohn's disease in 350 cases and 350 controls. Through follow-up genotyping of 70 rare and low-frequency protein-altering variants in nine independent case-control series (16,054 Crohn's disease cases, 12,153 ulcerative colitis cases and 17,575 healthy controls), we identified four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association with a protective splice variant in CARD9 (P < 1 × 10(-16), odds ratio ≈ 0.29) and additional associations with coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by identifying new, rare and probably functional variants that could aid functional experiments and predictive models.     

Comparing strategies to fine-map the association of common SNPs at chromosome 9p21 with type 2 diabetes and myocardial infarction

Noncoding variants at human chromosome 9p21 near CDKN2A and CDKN2B are associated with type 2 diabetes, myocardial infarction, aneurysm, vertical cup disc ratio and at least five cancers. Here we compare approaches to more comprehensively assess genetic variation in the region. We carried out targeted sequencing at high coverage in 47 individuals and compared the results to pilot data from the 1000 Genomes Project. We imputed variants into type 2 diabetes and myocardial infarction cohorts directly from targeted sequencing, from a genotyped reference panel derived from sequencing and from 1000 Genomes Project low-coverage data. Polymorphisms with frequency >5% were captured well by all strategies. Imputation of intermediate-frequency polymorphisms required a higher density of tag SNPs in disease samples than is available on first-generation genome-wide association study (GWAS) arrays. Our association analyses identified more comprehensive sets of variants showing equivalent statistical association with type 2 diabetes or myocardial infarction, but did not identify stronger associations than the original GWAS signals.