Identification of Glycosylated Subtypes of Interferon-α Produced by Human Leukocytes

We found that interferon-α produced by human leukocytes contained four subtypes that were glycosylated by N-linkages according to the results of lectin blot analysis. These glycosylated subtypes were type H or type ω and thei sugar moieties had no relation to their biological activities.     

NEMO specifically recognizes K63‐linked poly‐ubiquitin chains through a new bipartite ubiquitin‐binding domain

An important property of NEMO, the core element of the IKK complex involved in NF‐κB activation, resides in its ability to specifically recognize poly‐ubiquitin chains. A small domain called NOA/UBAN has been suggested to be responsible for this property. We recently demonstrated that the C‐terminal Zinc Finger (ZF) of NEMO is also able to bind ubiquitin. We show here by ZF swapping and mutagenesis that this represents its only function. While neither NOA nor ZF shows any preference for K63‐linked chains, we demonstrate that together they form a bipartite high‐affinity K63‐specific ubiquitin‐binding domain. A similar domain can be found in two other proteins, Optineurin and ABIN2, and can be freely exchanged with that of NEMO without interfering with its activity. This suggests that the main function of the C‐terminal half of NEMO is to specifically bind K63‐linked poly‐ubiquitin chains. We also demonstrate that the recently described binding of NEMO to linear poly‐ubiquitin chains is dependent on the NOA alone and does not require the presence of the ZF.     

Bivariate versus multivariate allometry: A note on a paper by Jungers and German

Jungers and German (1981) found differences when they compared 1) coefficients of allometry from bivariate plots of log measurements versus log body weight with 2) those coefficients from the first principal component of the log measurements excluding body weight. It is argued here that an arbitrary choice of unit for “internal size” is all that separates these coefficients. When the unit is chosen to make internal size isometric with body weight the coefficients agree rather well.     

Application of common predictive habitat techniques for post-border weed risk management

Weed risk assessment has become an accepted methodology for examining the likelihood and consequence of a plant species becoming invasive outside of its native range. Weed risk assessment draws upon biological and ecological information to estimate the likelihood and magnitude of the threats posed by introducing non-indigenous plants. In geographical terms, this has traditionally been understood as within a new country following importation of plant material. However, recent risk assessment development has focused more specifically on intracountry risk posed by already-present invasive plants and is referred to as post-border weed risk management. This form of assessment calls for fine-scale predictions of invasive species habitat suitability. This study applies some of the more popular and widely available habitat prediction models that represent a variety of different statistical approaches (linear regression, logistic regression, Bayesian probability, Classification and Regression Trees, Genetic Algorithm for Rule-set Production) to a single invasive plant, the vertebrate-dispersed, fleshy fruited European olive ( Olea europaea L.) in southern Australia. The relationships between the dependant ( O. europaea distribution) and independent (soil and climate) variables are used in the models to produce predictive maps for each model. Accuracy was calculated for each model output as well as a combined surface to examine whether recent calls for ensemble modelling of distributions produces improved predictions. Overall, the combined prediction demonstrated superior accuracy compared to any individual model outputs. The combined outputs can be likened to mapped gradations of predicted habitat suitability. The type of output produced in this study should form a critical component of post-border weed risk management but more importantly, the methodology will add to this important discipline.