Linking C5 deficiency to an exonic splicing enhancer mutation

As an important component of the innate immune system, complement provides the initial response to prevent infections by pathogenic microorganisms. Patients with dysfunction of C5 display a propensity for severe recurrent infections. In this study, we present a patient with C5 deficiency demonstrated by immunochemical and functional analyses. Direct sequencing of all C5 exons displayed no mutation of obvious functional significance, except for an A to G transition in exon 10 predicting an exchange from lysine to arginine. This sequence alteration was present in only one allele of family members with a reduced serum C5 concentration and in both alleles of the patient with almost complete C5 deficiency, suggesting that this alteration may be producing the phenotype. Recent findings indicate that distinct nucleotide sequences, termed exonic splicing enhancers (ESEs), influence the splicing process. cDNA from all family members harboring the mutated allele showed skipping of exon 10, which resulted in a premature STOP codon, explaining the lack of C5 in the propositus. Sequence analysis of the mutated region revealed the substitution to be located within an ESE, as predicted by the RESCUE-ESE program. The altered ESE sequence is located close to the 5' splicing site and also lowers the predicted strength of the splice site itself. This apparently inconsequential sequence alteration represents a noncanonical splicing mutation altering an ESE. Our finding sheds a new light on the role of putative silent/conservative mutations in disease-associated genes.     

Fuel Economy and Greenhouse Gas Emissions Labeling for Plug‐In Hybrid Vehicles from a Life Cycle Perspective

Fuel economy has been an effective indicator of vehicle greenhouse gas (GHG) emissions for conventional gasoline‐powered vehicles due to the strong relationship between fuel economy and vehicle life cycle emissions. However, fuel economy is not as accurate an indicator of vehicle GHG emissions for plug‐in hybrid (PHEVs) and pure battery electric vehicles (EVs). Current vehicle labeling efforts by the U.S. Environmental Protection Agency (EPA) and Department of Transportation have been focused on providing energy and environmental information to consumers based on U.S. national average data. This article explores the effects of variations in regional grids and regional daily vehicle miles traveled (VMT) on the total vehicle life cycle energy and GHG emissions of electrified vehicles and compare these results with information reported on the label and on the EPA's fuel economy Web site. The model results suggest that only 25% of the life cycle emissions from a representative PHEV are reflected on current vehicle labeling. The results show great variation in total vehicle life cycle emissions due to regional grid differences, including an approximately 100 gram per mile life cycle GHG emissions difference between the lowest and highest electric grid regions and up to a 100% difference between the state‐specific emission values within the same electric grid regions. Unexpectedly, for two regional grids the life cycle GHG emissions were higher in electric mode than in gasoline mode. We recommend that labels include stronger language on their deficiencies and provide ranges for GHG emissions from vehicle charging in regional electricity grids to better inform consumers.     

Single Cell Measurement of Dopamine Release with Simultaneous Voltage-clamp and Amperometry

After its release into the synaptic cleft, dopamine exerts its biological properties via its pre- and post-synaptic targets¹. The dopamine signal is terminated by diffusion^2-3, extracellular enzymes⁴, and membrane transporters⁵. The dopamine transporter, located in the peri-synaptic cleft of dopamine neurons clears the released amines through an inward dopamine flux (uptake). The dopamine transporter can also work in reverse direction to release amines from inside to outside in a process called outward transport or efflux of dopamine⁵. More than 20 years ago Sulzer et al. reported the dopamine transporter can operate in two modes of activity: forward (uptake) and reverse (efflux)⁵. The neurotransmitter released via efflux through the transporter can move a large amount of dopamine to the extracellular space, and has been shown to play a major regulatory role in extracellular dopamine homeostasis⁶. Here we describe how simultaneous patch clamp and amperometry recording can be used to measure released dopamine via the efflux mechanism with millisecond time resolution when the membrane potential is controlled. For this, whole-cell current and oxidative (amperometric) signals are measured simultaneously using an Axopatch 200B amplifier (Molecular Devices, with a low-pass Bessel filter set at 1,000 Hz for whole-cell current recording). For amperometry recording a carbon fiber electrode is connected to a second amplifier (Axopatch 200B) and is placed adjacent to the plasma membrane and held at +700 mV. The whole-cell and oxidative (amperometric) currents can be recorded and the current-voltage relationship can be generated using a voltage step protocol. Unlike the usual amperometric calibration, which requires conversion to concentration, the current is reported directly without considering the effective volume⁷. Thus, the resulting data represent a lower limit to dopamine efflux because some transmitter is lost to the bulk solution.     

Combining capture–recapture data and known ages allows estimation of age‐dependent survival rates

In many animal populations, demographic parameters such as survival and recruitment vary markedly with age, as do parameters related to sampling, such as capture probability. Failing to account for such variation can result in biased estimates of population‐level rates. However, estimating age‐dependent survival rates can be challenging because ages of individuals are rarely known unless tagging is done at birth. For many species, it is possible to infer age based on size. In capture–recapture studies of such species, it is possible to use a growth model to infer the age at first capture of individuals. We show how to build estimates of age‐dependent survival into a capture–mark–recapture model based on data obtained in a capture–recapture study. We first show how estimates of age based on length increments closely match those based on definitive aging methods. In simulated analyses, we show that both individual ages and age‐dependent survival rates estimated from simulated data closely match true values. With our approach, we are able to estimate the age‐specific apparent survival rates of Murray and trout cod in the Murray River, Australia. Our model structure provides a flexible framework within which to investigate various aspects of how survival varies with age and will have extensions within a wide range of ecological studies of animals where age can be estimated based on size.     

The Novel 10-Item Asthma Prediction Tool: External Validation in the German MAS Birth Cohort

Background

A novel non-invasive asthma prediction tool from the Leicester Cohort, UK, forecasts asthma at age 8 years based on 10 predictors assessed in early childhood, including current respiratory symptoms, eczema, and parental history of asthma.

Objective

We aimed to externally validate the proposed asthma prediction method in a German birth cohort.

Methods

The MAS-90 study (Multicentre Allergy Study) recorded details on allergic diseases prospectively in about yearly follow-up assessments up to age 20 years in a cohort of 1,314 children born 1990. We replicated the scoring method from the Leicester cohort and assessed prediction, performance and discrimination. The primary outcome was defined as the combination of parent-reported wheeze and asthma drugs (both in last 12 months) at age 8. Sensitivity analyses assessed model performance for outcomes related to asthma up to age 20 years.

Results

For 140 children parents reported current wheeze or cough at age 3 years. Score distribution and frequencies of later asthma resembled the Leicester cohort: 9% vs. 16% (MAS-90 vs. Leicester) of children at low risk at 3 years had asthma at 8 years, at medium risk 45% vs. 48%. Performance of the asthma prediction tool in the MAS-90 cohort was similar (Brier score 0.22 vs. 0.23) and discrimination slightly better than in the original cohort (area under the curve, AUC 0.83 vs. 0.78). Prediction and discrimination were robust against changes of inclusion criteria, scoring and outcome definitions. The secondary outcome ‘physicians’ diagnosed asthma at 20 years'' showed the highest discrimination (AUC 0.89).

Conclusion

The novel asthma prediction tool from the Leicester cohort, UK, performed well in another population, a German birth cohort, supporting its use and further development as a simple aid to predict asthma risk in clinical settings.