Structural comparison of fibroblast growth factor-specific heparan sulfates derived from a growing or differentiating neuroepithelial cell line

Heparan sulfate (HS) glycosaminoglycans are essential modulators of fibroblast growth factor (FGF) activity both in vivo and in vitro, and appear to act by cross-linking particular forms of FGF to appropriate FGF receptors. We have recently isolated and characterized two separate HS pools derived from immortalized embryonic day 10 mouse neuroepithelial 2.3D cells: one from cells in log growth phase, which greatly potentiates the activity of FGF-2, and the other from cells undergoing contact-inhibition and differentiation, which preferentially activates FGF-1. These two pools of HS have very similar functional activities to those species isolated from primary neuroepithelial cells at corresponding stages of active proliferation or differentiation. We present here a structural comparison between these cell line HS species to establish the nature of the changes that occur in the biosynthesis of HS. A combination of chemical and enzymatic cleavage, low pressure chromatography and strong anion-exchange HPLC were used to generate full chain models of each species. Overall, the HS pools synthesized in the dividing cell line pools possessed less complex sulfation than those derived from more differentiated, growth arrested cells.      

Structural requirements for efficient prion protein conversion: Cofactors may promote a conversion-competent structure for PrPC

To understand why cross-species infection of prion disease often results in inefficient transmission and reduced protein conversion, most research has focused on defining the effect of variations in PrP primary structures, including sequence compatibility of substrate and seed. By contrast, little research has been aimed at investigating structural differences between different variants of PrP^C and secondary structural requirements for efficient conversion. This is despite a clear role for molecular chaperones in formation of prions in non-mammalian systems, indicating the importance of secondary/tertiary structure during the conversion process. Recent data from our laboratory on the cellular location of disease-specific prion cofactors supports the critical role of specific secondary structural motifs and the stability of these motifs in determining the efficiency of disease-specific prion protein conversion. In this paper we summarize our recent results and build on the hypothesis previously suggested by Wuthrich and colleagues, that stability of certain regions of the prion protein is crucial for protein conversion to abnormal isoforms in vivo. It is suggested that one role for molecular cofactors in the conversion process is to stabilize PrP^C structure in a form that is amenable for conversion to PrP^Sc.Key words: cofactor, structure, cell-free conversion assay, fibrillization, stability, loop region     

A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

Background  

Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear.     

Maps of the Sri Lanka malaria situation preceding the tsunami and key aspects to be considered in the emergency phase and beyond

In Vietnam, a large proportion of all malaria cases and deaths occurs in the central mountainous and forested part of the country. Indeed, forest malaria, despite intensive control activities, is still a major problem which raises several questions about its dynamics. A large-scale malaria morbidity survey to measure malaria endemicity and identify important risk factors was carried out in 43 villages situated in a forested area of Ninh Thuan province, south central Vietnam. Four thousand three hundred and six randomly selected individuals, aged 10–60 years, participated in the survey. Rag Lays (86%), traditionally living in the forest and practising "slash and burn" cultivation represented the most common ethnic group. The overall parasite rate was 13.3% (range [0–42.3] while Plasmodium falciparum seroprevalence was 25.5% (range [2.1–75.6]). Mapping of these two variables showed a patchy distribution, suggesting that risk factors other than remoteness and forest proximity modulated the human-vector interactions. This was confirmed by the results of the multivariate-adjusted analysis, showing that forest work was a significant risk factor for malaria infection, further increased by staying in the forest overnight (OR= 2.86; 95%CI [1.62; 5.07]). Rag Lays had a higher risk of malaria infection, which inversely related to education level and socio-economic status. Women were less at risk than men (OR = 0.71; 95%CI [0.59; 0.86]), a possible consequence of different behaviour. This study confirms that malaria endemicity is still relatively high in this area and that the dynamics of transmission is constantly modulated by the behaviour of both humans and vectors. A well-targeted intervention reducing the "vector/forest worker" interaction, based on long-lasting insecticidal material, could be appropriate in this environment.     

Exploratory Analysis of Methods for Automated Classification of Laboratory Test Orders into Syndromic Groups in Veterinary Medicine

Background

Recent focus on earlier detection of pathogen introduction in human and animal populations has led to the development of surveillance systems based on automated monitoring of health data. Real- or near real-time monitoring of pre-diagnostic data requires automated classification of records into syndromes–syndromic surveillance–using algorithms that incorporate medical knowledge in a reliable and efficient way, while remaining comprehensible to end users.

Methods

This paper describes the application of two of machine learning (Naïve Bayes and Decision Trees) and rule-based methods to extract syndromic information from laboratory test requests submitted to a veterinary diagnostic laboratory.

Results

High performance (F₁-macro = 0.9995) was achieved through the use of a rule-based syndrome classifier, based on rule induction followed by manual modification during the construction phase, which also resulted in clear interpretability of the resulting classification process. An unmodified rule induction algorithm achieved an F_1-micro score of 0.979 though this fell to 0.677 when performance for individual classes was averaged in an unweighted manner (F_1-macro), due to the fact that the algorithm failed to learn 3 of the 16 classes from the training set. Decision Trees showed equal interpretability to the rule-based approaches, but achieved an F_1-micro score of 0.923 (falling to 0.311 when classes are given equal weight). A Naïve Bayes classifier learned all classes and achieved high performance (F_1-micro = 0.994 and F_1-macro = .955), however the classification process is not transparent to the domain experts.

Conclusion

The use of a manually customised rule set allowed for the development of a system for classification of laboratory tests into syndromic groups with very high performance, and high interpretability by the domain experts. Further research is required to develop internal validation rules in order to establish automated methods to update model rules without user input.     

Two-Photon-Based Photoactivation in Live Zebrafish Embryos

Photoactivation of target compounds in a living organism has proven a valuable approach to investigate various biological processes such as embryonic development, cellular signaling and adult physiology. In this respect, the use of multi-photon microscopy enables quantitative photoactivation of a given light responsive agent in deep tissues at a single cell resolution. As zebrafish embryos are optically transparent, their development can be monitored in vivo. These traits make the zebrafish a perfect model organism for controlling the activity of a variety of chemical agents and proteins by focused light. Here we describe the use of two-photon microscopy to induce the activation of chemically caged fluorescein, which in turn allows us to follow cell''s destiny in live zebrafish embryos. We use embryos expressing a live genetic landmark (GFP) to locate and precisely target any cells of interest. This procedure can be similarly used for precise light induced activation of proteins, hormones, small molecules and other caged compounds.Download video file.^{(57M, mov)}