Identifying foldable regions in protein sequence from the hydrophobic signal

Structural genomics initiatives aim to elucidate representative 3D structures for the majority of protein families over the next decade, but many obstacles must be overcome. The correct design of constructs is extremely important since many proteins will be too large or contain unstructured regions and will not be amenable to crystallization. It is therefore essential to identify regions in protein sequences that are likely to be suitable for structural study. Scooby-Domain is a fast and simple method to identify globular domains in protein sequences. Domains are compact units of protein structure and their correct delineation will aid structural elucidation through a divide-and-conquer approach. Scooby-Domain predictions are based on the observed lengths and hydrophobicities of domains from proteins with known tertiary structure. The prediction method employs an A*-search to identify sequence regions that form a globular structure and those that are unstructured. On a test set of 173 proteins with consensus CATH and SCOP domain definitions, Scooby-Domain has a sensitivity of 50% and an accuracy of 29%, which is better than current state-of-the-art methods. The method does not rely on homology searches and, therefore, can identify previously unknown domains.

Chronic stress alters the density and morphology of microglia in a subset of stress-responsive brain regions

The current study, in parallel experiments, evaluated the impact of chronic psychological stress on physiological and behavioural measures, and on the activation status of microglia in 15 stress-responsive brain regions. Rats were subjected, for 14 days, to two 30 min sessions of restraint per day, applied at random times each day. In one experiment the effects of stress on sucrose preference, weight gain, core body temperature, and struggling behaviour during restraint, were determined. In the second experiment we used immunohistochemistry to investigate stress-induced changes in ionized calcium-binding adaptor molecule-1 (Iba1), a marker constitutively expressed by microglia, and major histocompatibility complex-II (MHC-II), a marker often expressed on activated microglia, in a total of 15 stress-responsive nuclei. We also investigated cellular proliferation in these regions using Ki67 immunolabelling, to check for the possibility of microglial proliferation. Collectively, the results we obtained showed that chronic stress induced a significant increase in anhedonia, a decrease in weight gain across the entire observation period, a significant elevation in core body temperature during restraint, and a progressive decrease in struggling behaviour within and over sessions. With regard to microglial activation, chronic stress induced a significant increase in the density of Iba1 immunolabelling (nine of 15 regions) and the number of Iba1-positive cells (eight of 15 regions). Within the regions that exhibited an increased number of Iba1-positive cells after chronic stress, we found no evidence of a between group difference in the number of MHC-II or Ki67 positive cells. In summary, these results clearly demonstrate that chronic stress selectively increases the number of microglia in certain stress-sensitive brain regions, and also causes a marked transition of microglia from a ramified-resting state to a non-resting state. These findings are consistent with the view that microglial activation could play an important role in controlling and/or adapting to stress.

Combining image regions and human activity for indirect object recognition in indoor wide-angle views

Traditional methods of object recognition are reliant on shape and so are very difficult to apply in cluttered, wideangle and low-detail views such as surveillance scenes. To address this, a method of indirect object recognition is proposed, where human activity is used to infer both the location and identity of objects. No shape analysis is necessary. The concept is dubbed 'interaction signatures', since the premise is that a human will interact with objects in ways characteristic of the function of that object - for example, a person sits in a chair and drinks from a cup. The human-centred approach means that recognition is possible in low-detail views and is largely invariant to the shape of objects within the same functional class. This paper implements a Bayesian network for classifying region patches with object labels, building upon our previous work in automatically segmenting and recognising a human's interactions with the objects. Experiments show that interaction signatures can successfully find and label objects in low-detail views and are equally effective at recognising test objects that differ markedly in appearance from the training objects.

Book review : Entrepreneurship in emerging regions around the world : theory, evidence and implications

P.H. Phan, S. Venkataraman and S.R. Velamuri (2008) Entrepreneurship in emerging regions around the world: Theory, evidence and implications, Edward Elgar, Cheltenham, United Kingdom

Mortality disparities between geographic regions : results from a risk percentiles model for coronary heart disease

Background: Planning of disease prevention strategies requires information regarding the distribution of absolute risk in the population to allow targeting of people at high disease risk. It is well known that death rates from coronary heart disease (CHD) are higher in remote areas of Australia compared with major cities. Less well understood is the distribution of the absolute risk of CHD death within the different geographic regions. We present a mathematical model of CHD which projects the lifetime risk of death among individuals in different percentiles of CHD risk. We apply this to model the distribution of CHD risk within different geographic regions.

Methods: Using information from the Framingham1, MRFIT2 and AusDiab3 studies, the Australian population was divided into percentiles of CHD risk within age and gender groups by geographic location. Absolute mortality risk was determined at each percentile using current Australian mortality data. Survival curves were generated for each percentile using these risk estimates. Approximate confidence intervals were derived using bootstrap methods.

Conclusions: The difference in life expectancy at age 25 between those in the lowest decile of CHD risk compared to the highest was 5.8 years (95%CI:4.7,6.7) in major cities compared to 8.5 years (95%CI:7.6,9.7) in remote areas. The difference in risk of premature death (before age 75) was 12% (95%CI:10%,14%) in major cities compared to 33% (95%CI:28%,38%) in remote areas.