Children with sickle cell anemia with normal TCD and without silent infarcts have a low incidence of new strokes

In a prospective cohort study, we tested the hypothesis that children with sickle cell anemia (SCA) with normal transcranial Doppler ultrasound (TCD) velocities and without silent cerebral infarcts (SCIs) would have a lower incidence rate of new neurological events (strokes, seizures or transient ischemic attacks) compared to children with normal TCD measurements and SCIs, not receiving regular blood transfusions. Non-randomized participants from the Silent Cerebral Infarct Transfusion (SIT) Trial who had screening magnetic resonance imaging (MRI) of the brain and normal TCD measurements were included. Follow-up ended at the time of first neurological event, start of regular blood transfusion, or loss to follow-up, whichever came first. The primary endpoint was a new neurological event. Of 421 participants included, 68 had suspected SCIs. Mean follow-up was 3.6 years. Incidence rates of new neurological events in non-transfused participants with normal TCD values with SCIs and without SCIs were 1.71 and 0.47 neurological events per 100 patient-years, respectively, p=0.065. The absence of SCI(s) at baseline was associated with a decreased risk of a new neurological event (hazard ratio 0.231, 95% CI 0.062 - 0.858; p=0.029). Local pediatric neurologists examined 67 of 68 participants with suspected SCIs and identified 2 with overt strokes classified as SCIs by local hematologists; subsequently one had a seizure and the other an ischemic stroke. Children with SCA, without SCIs, and normal TCD measurements have a significantly lower rate of new neurological events when compared to those with SCIs and normal TCD measurements. Pediatric neurology assessment may assist risk stratification. This article is protected by copyright. All rights reserved

Mechanisms Underlying Stage-1 TRPL Channel Translocation in Drosophila Photoreceptors

Background: TRP channels function as key mediators of sensory transduction and other cellular signaling pathways. In Drosophila, TRP and TRPL are the light-activated channels in photoreceptors. While TRP is statically localized in the signaling compartment of the cell (the rhabdomere), TRPL localization is regulated by light. TRPL channels translocate out of the rhabdomere in two distinct stages, returning to the rhabdomere with dark-incubation. Translocation of TRPL channels regulates their availability, and thereby the gain of the signal. Little, however, is known about the mechanisms underlying this trafficking of TRPL channels. Methodology/Principal Findings: We first examine the involvement of de novo protein synthesis in TRPL translocation. We feed flies cycloheximide, verify inhibition of protein synthesis, and test for TRPL translocation in photoreceptors. We find that protein synthesis is not involved in either stage of TRPL translocation out of the rhabdomere, but that re-localization to the rhabdomere from stage-1, but not stage-2, depends on protein synthesis. We also characterize an ex vivo eye preparation that is amenable to biochemical and genetic manipulation. We use this preparation to examine mechanisms of stage-1 TRPL translocation. We find that stage-1 translocation is: induced with ATP depletion, unaltered with perturbation of the actin cytoskeleton or inhibition of endocytosis, and slowed with increased membrane sterol content. Conclusions/Significance: Our results indicate that translocation of TRPL out of the rhabdomere is likely due to protei

Immunogenicity and Protective Capacity of a Virosomal Respiratory Syncytial Virus Vaccine Adjuvanted with Monophosphoryl Lipid A in Mice

Respiratory Syncytial Virus (RSV) is a major cause of viral brochiolitis in infants and young children and is also a significant problem in elderly and immuno-compromised adults. To date there is no efficacious and safe RSV vaccine, partially because of the outcome of a clinical trial in the 1960s with a formalin-inactivated RSV vaccine (FI-RSV). This vaccine caused enhanced respiratory disease upon exposure to the live virus, leading to increased morbidity and the death of two children. Subsequent analyses of this incident showed that FI-RSV induces a Th2-skewed immune response together with poorly neutralizing antibodies. As a new approach, we used reconstituted RSV viral envelopes, i.e. virosomes, with incorporated monophosphoryl lipid A (MPLA) adjuvant to enhance immunogenicity and to skew the immune response towards a Th1 phenotype. Incorporation of MPLA stimulated the overall immunogenicity of the virosomes compared to non-adjuvanted virosomes in mice. Intramuscular administration of the vaccine led to the induction of RSV-specific IgG2a levels similar to those induced by inoculation of the animals with live RSV. These antibodies were able to neutralize RSV in vitro. Furthermore, MPLA-adjuvanted RSV virosomes induced high amounts of IFNγ and low amounts of IL5 in both spleens and lungs of immunized and subsequently challenged animals, compared to levels of these cytokines in animals vaccinated with FI-RSV, indicating a Th1-skewed response. Mice vaccinated with RSV-MPLA virosomes were protected from live RSV challenge, clearing the inoculated virus without showing signs of lung pathology. Taken together, these data demonstrate that RSV-MPLA virosomes represent a safe and efficacious vaccine candidate which warrants further evaluation

Multiparameter Telemetry as a Sensitive Screening Method to Detect Vaccine Reactogenicity in Mice

Refined vaccines and adjuvants are urgently needed to advance immunization against global infectious challenges such as HIV, hepatitis C, tuberculosis and malaria. Large-scale screening efforts are ongoing to identify adjuvants with improved efficacy profiles. Reactogenicity often represents a major hurdle to the clinical use of new substances. Yet, irrespective of its importance, this parameter has remained difficult to screen for, owing to a lack of sensitive small animal models with a capacity for high throughput testing. Here we report that continuous telemetric measurements of heart rate, heart rate variability, body core temperature and locomotor activity in laboratory mice readily unmasked systemic side-effects of vaccination, which went undetected by conventional observational assessment and clinical scoring. Even minor aberrations in homeostasis were readily detected, ranging from sympathetic activation over transient pyrogenic effects to reduced physical activity and apathy. Results in real-time combined with the potential of scalability and partial automation in the industrial context suggest multiparameter telemetry in laboratory mice as a first-line screen for vaccine reactogenicity. This may accelerate vaccine discovery in general and may further the success of vaccines in combating infectious disease and cancer

Epistasis: Obstacle or Advantage for Mapping Complex Traits?

Identification of genetic loci in complex traits has focused largely on one-dimensional genome scans to search for associations between single markers and the phenotype. There is mounting evidence that locus interactions, or epistasis, are a crucial component of the genetic architecture of biologically relevant traits. However, epistasis is often viewed as a nuisance factor that reduces power for locus detection. Counter to expectations, recent work shows that fitting full models, instead of testing marker main effect and interaction components separately, in exhaustive multi-locus genome scans can have higher power to detect loci when epistasis is present than single-locus scans, and improvement that comes despite a much larger multiple testing alpha-adjustment in such searches. We demonstrate, both theoretically and via simulation, that the expected power to detect loci when fitting full models is often larger when these loci act epistatically than when they act additively. Additionally, we show that the power for single locus detection may be improved in cases of epistasis compared to the additive model. Our exploration of a two step model selection procedure shows that identifying the true model is difficult. However, this difficulty is certainly not exacerbated by the presence of epistasis, on the contrary, in some cases the presence of epistasis can aid in model selection. The impact of allele frequencies on both power and model selection is dramatic

Predicting Unobserved Phenotypes for Complex Traits from Whole-Genome SNP Data

Genome-wide association studies (GWAS) for quantitative traits and disease in humans and other species have shown that there are many loci that contribute to the observed resemblance between relatives. GWAS to date have mostly focussed on discovery of genes or regulatory regions habouring causative polymorphisms, using single SNP analyses and setting stringent type-I error rates. Genome-wide marker data can also be used to predict genetic values and therefore predict phenotypes. Here, we propose a Bayesian method that utilises all marker data simultaneously to predict phenotypes. We apply the method to three traits: coat colour, %CD8 cells, and mean cell haemoglobin, measured in a heterogeneous stock mouse population. We find that a model that contains both additive and dominance effects, estimated from genome-wide marker data, is successful in predicting unobserved phenotypes and is significantly better than a prediction based upon the phenotypes of close relatives. Correlations between predicted and actual phenotypes were in the range of 0.4 to 0.9 when half of the number of families was used to estimate effects and the other half for prediction. Posterior probabilities of SNPs being associated with coat colour were high for regions that are known to contain loci for this trait. The prediction of phenotypes using large samples, high-density SNP data, and appropriate statistical methodology is feasible and can be applied in human medicine, forensics, or artificial selection programs

Causal inference based on counterfactuals

BACKGROUND: The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. DISCUSSION: This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. SUMMARY: Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept

GIS and spatial data analysis: Converging perspectives

We take as our starting point the state of geographic information systems (GIS) and spatial data analysis 50 years ago when regional science emerged as a new field of enquiry. In the late 1950s and 1960s advances in computing technology were making possible forms of automated cartography that in due course would lead to th