Bacterial endotoxins: biological properties and mechanisms of action

Endotoxins (lipopolysaccharides, LPS) are agents of pathogenicity of Gram-negative bacteria, implicated in the development of Gram-negative shock. Endotoxin reacts with lipopolysaccharide-sensitive cells producing endogenous mediators such as tumour necrosis factor alpha (TNFα). Macrophages are cells mediating the toxic activities of LPS and TNFα is the primary mediator of the lethal action of endotoxin. This review article discusses the various mechanisms by which endotoxin hypersensitivity in bacteria-sensitized animals develops. The paper concludes with a discussion on the possible protective effect of carnitine congeners against the lethal action of LPS

A non-destructive view with X-rays into the strain state of bronze axes.

In this paper we present a new approach using highly surface sensitive X-ray diffraction methods for archaeometrical investigation highlighted on the Neolithic Axe of Ahneby. Applying the sin2Ψ-method with a scintillation detector and a MAXIM camera setup, both usually applied for material strain analysis on modern metal fabrics. We can distinguish between different production states of bronze axes: Cast, forged and tempered. The method can be applied as a local probe of some 100th of μm2 or integrative on a square centimeter surface area. We applied established synchrotron radiation based methods of material strain mapping and diffraction on a Neolithic bronze axe as well as replicated material for noninvasive analysis. The main goal of the described investigations was to identify the effects upon the bronze objects of post cast surface treatment with stone tools and of heat treatment

A semi-parametric Bayesian model for unsupervised differential co-expression analysis

<p>Abstract</p> <p>Background</p> <p>Differential co-expression analysis is an emerging strategy for characterizing disease related dysregulation of gene expression regulatory networks. Given pre-defined sets of biological samples, such analysis aims at identifying genes that are co-expressed in one, but not in the other set of samples.</p> <p>Results</p> <p>We developed a novel probabilistic framework for jointly uncovering contexts (i.e. groups of samples) with specific co-expression patterns, and groups of genes with different co-expression patterns across such contexts. In contrast to current clustering and bi-clustering procedures, the implicit similarity measure in this model used for grouping biological samples is based on the clustering structure of genes within each sample and not on traditional measures of gene expression level similarities. Within this framework, biological samples with widely discordant expression patterns can be placed in the same context as long as the co-clustering structure of genes is concordant within these samples. To the best of our knowledge, this is the first method to date for unsupervised differential co-expression analysis in this generality. When applied to the problem of identifying molecular subtypes of breast cancer, our method identified reproducible patterns of differential co-expression across several independent expression datasets. Sample groupings induced by these patterns were highly informative of the disease outcome. Expression patterns of differentially co-expressed genes provided new insights into the complex nature of the ER<it>α </it>regulatory network.</p> <p>Conclusions</p> <p>We demonstrated that the use of the co-clustering structure as the similarity measure in the unsupervised analysis of sample gene expression profiles provides valuable information about expression regulatory networks.</p

WebGimm: An integrated web-based platform for cluster analysis, functional analysis, and interactive visualization of results

Cluster analysis methods have been extensively researched, but the adoption of new methods is often hindered by technical barriers in their implementation and use. WebGimm is a free cluster analysis web-service, and an open source general purpose clustering web-server infrastructure designed to facilitate easy deployment of integrated cluster analysis servers based on clustering and functional annotation algorithms implemented in R. Integrated functional analyses and interactive browsing of both, clustering structure and functional annotations provides a complete analytical environment for cluster analysis and interpretation of results. The Java Web Start client-based interface is modeled after the familiar cluster/treeview packages making its use intuitive to a wide array of biomedical researchers. For biomedical researchers, WebGimm provides an avenue to access state of the art clustering procedures. For Bioinformatics methods developers, WebGimm offers a convenient avenue to deploy their newly developed clustering methods. WebGimm server, software and manuals can be freely accessed at http://ClusterAnalysis.org/

Annotation concept synthesis and enrichment analysis: a logic-based approach to the interpretation of high-throughput experiments

Motivation: Annotation Enrichment Analysis (AEA) is a widely used analytical approach to process data generated by high-throughput genomic and proteomic experiments such as gene expression microarrays. The analysis uncovers and summarizes discriminating background information (e.g. GO annotations) for sets of genes identified by experiments (e.g. a set of differentially expressed genes, a cluster). The discovered information is utilized by human experts to find biological interpretations of the experiments

Annotation concept synthesis and enrichment analysis: a logic-based approach to the interpretation of high-throughput experiments

Motivation: Annotation Enrichment Analysis (AEA) is a widely used analytical approach to process data generated by high-throughput genomic and proteomic experiments such as gene expression microarrays. The analysis uncovers and summarizes discriminating background information (e.g. GO annotations) for sets of genes identified by experiments (e.g. a set of differentially expressed genes, a cluster). The discovered information is utilized by human experts to find biological interpretations of the experiments

Bio-responsive polymer hydrogels homeostatically regulate blood coagulation

Bio-responsive polymer architectures can empower medical therapies by engaging molecular feedback-response mechanisms resembling the homeostatic adaptation of living tissues to varying environmental constraints. Here we show that a blood coagulation-responsive hydrogel system can deliver heparin in amounts triggered by the environmental levels of thrombin, the key enzyme of the coagulation cascade, which - in turn - becomes inactivated due to released heparin. The bio-responsive hydrogel quantitatively quenches blood coagulation over several hours in the presence of pro-coagulant stimuli and during repeated incubation with fresh, non-anticoagulated blood. These features enable the introduced material to provide sustainable, autoregulated anticoagulation, addressing a key challenge of many medical therapies. Beyond that, the explored concept may facilitate the development of materials that allow the effective and controlled application of drugs and biomolecules

Understanding students’ motivation towards proactive career behaviours through goal-setting theory and the job demands–resources model

The graduate labour market is highly competitive but little is known about why students vary in their development of employability. This study contributes to the literature by applying goal-setting theory and the job demands–resources model to investigate how motivational processes influence students’ proactive career behaviours. We tested four hypotheses using structural equation modelling and moderation/mediation analysis using a nested model approach; 432 undergraduates from 21 UK universities participated in this cross-sectional study. The results showed that students higher in mastery approach had greater perceived employability mediated by two proactive career behaviours (skill development and network building). Students’ career goal commitment was associated with all four proactive career behaviours (career planning, skill development, career consultation and network building). Students’ academic and employment workloads did not negatively impact their proactive career behaviours. University tutors and career services should therefore encourage students to set challenging career goals that reflect mastery approach