The iBRA (implant breast reconstruction evaluation) study: protocol for a prospective multi-centre cohort study to inform the feasibility, design and conduct of a pragmatic randomised clinical trial comparing new techniques of implant-based breast reconstruction.

BACKGROUND: Implant-based breast reconstruction (IBBR) is the most commonly performed reconstructive procedure in the UK. The introduction of techniques to augment the subpectoral pocket has revolutionised the procedure, but there is a lack of high-quality outcome data to describe the safety or effectiveness of these techniques. Randomised controlled trials (RCTs) are the best way of comparing treatments, but surgical RCTs are challenging. The iBRA (implant breast reconstruction evaluation) study aims to determine the feasibility, design and conduct of a pragmatic RCT to examine the effectiveness of approaches to IBBR. METHODS/DESIGN: The iBRA study is a trainee-led research collaborative project with four phases:Phase 1 - a national practice questionnaire (NPQ) to survey current practicePhase 2 - a multi-centre prospective cohort study of patients undergoing IBBR to evaluate the clinical and patient-reported outcomesPhase 3- an IBBR-RCT acceptability survey and qualitative work to explore patients' and surgeons' views of proposed trial designs and candidate outcomes.Phase 4 - phases 1 to 3 will inform the design and conduct of the future RCT All centres offering IBBR will be encouraged to participate by the breast and plastic surgical professional associations (Association of Breast Surgery and British Association of Plastic Reconstructive and Aesthetic Surgeons). Data collected will inform the feasibility of undertaking an RCT by defining current practice and exploring issues surrounding recruitment, selection of comparator arms, choice of primary outcome, sample size, selection criteria, trial conduct, methods of data collection and feasibility of using the trainee collaborative model to recruit patients and collect data. DISCUSSION: The preliminary work undertaken within the iBRA study will determine the feasibility, design and conduct of a definitive RCT in IBBR. It will work with the trainee collaborative to build capacity by creating an infrastructure of research-active breast and plastic surgeons which will facilitate future high-quality research that will ultimately improve outcomes for all women seeking reconstructive surgery. TRIAL REGISTRATION: ISRCTN37664281

A Minimal Model of Signaling Network Elucidates Cell-to-Cell Stochastic Variability in Apoptosis

Signaling networks are designed to sense an environmental stimulus and adapt to it. We propose and study a minimal model of signaling network that can sense and respond to external stimuli of varying strength in an adaptive manner. The structure of this minimal network is derived based on some simple assumptions on its differential response to external stimuli. We employ stochastic differential equations and probability distributions obtained from stochastic simulations to characterize differential signaling response in our minimal network model. We show that the proposed minimal signaling network displays two distinct types of response as the strength of the stimulus is decreased. The signaling network has a deterministic part that undergoes rapid activation by a strong stimulus in which case cell-to-cell fluctuations can be ignored. As the strength of the stimulus decreases, the stochastic part of the network begins dominating the signaling response where slow activation is observed with characteristic large cell-to-cell stochastic variability. Interestingly, this proposed stochastic signaling network can capture some of the essential signaling behaviors of a complex apoptotic cell death signaling network that has been studied through experiments and large-scale computer simulations. Thus we claim that the proposed signaling network is an appropriate minimal model of apoptosis signaling. Elucidating the fundamental design principles of complex cellular signaling pathways such as apoptosis signaling remains a challenging task. We demonstrate how our proposed minimal model can help elucidate the effect of a specific apoptotic inhibitor Bcl-2 on apoptotic signaling in a cell-type independent manner. We also discuss the implications of our study in elucidating the adaptive strategy of cell death signaling pathways.Comment: 9 pages, 6 figure

Protein profiles in Tc1 mice implicate novel pathway perturbations in the Down syndrome brain

Tc1 mouse model of Down syndrome (DS) is functionally trisomic for ∼120 human chromosome 21 (HSA21) classical protein-coding genes. Tc1 mice display features relevant to the DS phenotype, including abnormalities in learning and memory and synaptic plasticity. To determine the molecular basis for the phenotypic features, the levels of 90 phosphorylation-specific and phosphorylation-independent proteins were measured by Reverse Phase Protein Arrays in hippocampus and cortex, and 64 in cerebellum, of Tc1 mice and littermate controls. Abnormal levels of proteins involved in MAP kinase, mTOR, GSK3B and neuregulin signaling were identified in trisomic mice. In addition, altered correlations among the levels of N-methyl-D-aspartate (NMDA) receptor subunits and the HSA21 proteins amyloid beta (A4) precursor protein (APP) and TIAM1, and between immediate early gene (IEG) proteins and the HSA21 protein superoxide dismutase-1 (SOD1) were found in the hippocampus of Tc1 mice, suggesting altered stoichiometry among these sets of functionally interacting proteins. Protein abnormalities in Tc1 mice were compared with the results of a similar analysis of Ts65Dn mice, a DS mouse model that is trisomic for orthologs of 50 genes trisomic in the Tc1 plus an additional 38 HSA21 orthologs. While there are similarities, abnormalities unique to the Tc1 include increased levels of the S100B calcium-binding protein, mTOR proteins RAPTOR and P70S6, the AMP-kinase catalytic subunit AMPKA, the IEG proteins FBJ murine osteosarcoma viral oncogene homolog (CFOS) and activity-regulated cytoskeleton-associated protein (ARC), and the neuregulin 1 receptor ERBB4. These data identify novel perturbations, relevant to neurological function and to some seen in Alzheimer's disease, that may occur in the DS brain, potentially contributing to phenotypic features and influencing drug responses

A major genetic locus in <i>Trypanosoma brucei</i> is a determinant of host pathology

The progression and variation of pathology during infections can be due to components from both host or pathogen, and/or the interaction between them. The influence of host genetic variation on disease pathology during infections with trypanosomes has been well studied in recent years, but the role of parasite genetic variation has not been extensively studied. We have shown that there is parasite strain-specific variation in the level of splenomegaly and hepatomegaly in infected mice and used a forward genetic approach to identify the parasite loci that determine this variation. This approach allowed us to dissect and identify the parasite loci that determine the complex phenotypes induced by infection. Using the available trypanosome genetic map, a major quantitative trait locus (QTL) was identified on T. brucei chromosome 3 (LOD = 7.2) that accounted for approximately two thirds of the variance observed in each of two correlated phenotypes, splenomegaly and hepatomegaly, in the infected mice (named &lt;i&gt;TbOrg1&lt;/i&gt;). In addition, a second locus was identified that contributed to splenomegaly, hepatomegaly and reticulocytosis (&lt;i&gt;TbOrg2&lt;/i&gt;). This is the first use of quantitative trait locus mapping in a diploid protozoan and shows that there are trypanosome genes that directly contribute to the progression of pathology during infections and, therefore, that parasite genetic variation can be a critical factor in disease outcome. The identification of parasite loci is a first step towards identifying the genes that are responsible for these important traits and shows the power of genetic analysis as a tool for dissecting complex quantitative phenotypic traits

Fast cavity-enhanced atom detection with low noise and high fidelity

Cavity quantum electrodynamics describes the fundamental interactions between light and matter, and how they can be controlled by shaping the local environment. For example, optical microcavities allow high-efficiency detection and manipulation of single atoms. In this regime fluctuations of atom number are on the order of the mean number, which can lead to signal fluctuations in excess of the noise on the incident probe field. Conversely, we demonstrate that nonlinearities and multi-atom statistics can together serve to suppress the effects of atomic fluctuations when making local density measurements on clouds of cold atoms. We measure atom densities below 1 per cavity mode volume near the photon shot-noise limit. This is in direct contrast to previous experiments where fluctuations in atom number contribute significantly to the noise. Atom detection is shown to be fast and efficient, reaching fidelities in excess of 97% after 10 us and 99.9% after 30 us.Comment: 7 pages, 4 figures, 1 table; extensive changes to format and discussion according to referee comments; published in Nature Communications with open acces

Novel Role of Y1 Receptors in the Coordinated Regulation of Bone and Energy Homeostasis

The importance of neuropeptide Y (NPY) and Y2 receptors in the regulation of bone and energy homeostasis has recently been demonstrated. However, the contributions of the other Y recep- tors are less clear. Here we show that Y1 receptors are expressed on osteoblastic cells. Moreover, bone and adipose tissue mass are elevated in Y1/ mice with a generalized increase in bone formation on cortical and cancellous surfaces. Importantly, the inhibitory effects of NPY on bone marrow stromal cells in vitro are absent in cells derived from Y1/ mice, indicating a direct action of NPY on bone cells via this Y receptor. Interestingly, in contrast to Y2 receptor or germ line Y1 receptor deletion, con- ditional deletion of hypothalamic Y1 receptors in adult mice did not alter bone homeostasis, food intake, or adiposity. Further- more, deletion of both Y1 and Y2 receptors did not produce additive effects in bone or adiposity. Thus Y1 receptor pathways act powerfully to inhibit bone production and adiposity by non- hypothalamic pathways, with potentially direct effects on bone tissue through a single pathway with Y2 receptors

Evaluation of a Bayesian inference network for ligand-based virtual screening

Background Bayesian inference networks enable the computation of the probability that an event will occur. They have been used previously to rank textual documents in order of decreasing relevance to a user-defined query. Here, we modify the approach to enable a Bayesian inference network to be used for chemical similarity searching, where a database is ranked in order of decreasing probability of bioactivity. Results Bayesian inference networks were implemented using two different types of network and four different types of belief function. Experiments with the MDDR and WOMBAT databases show that a Bayesian inference network can be used to provide effective ligand-based screening, especially when the active molecules being sought have a high degree of structural homogeneity; in such cases, the network substantially out-performs a conventional, Tanimoto-based similarity searching system. However, the effectiveness of the network is much less when structurally heterogeneous sets of actives are being sought. Conclusion A Bayesian inference network provides an interesting alternative to existing tools for ligand-based virtual screening

Fast flowing populations are not well mixed

In evolutionary dynamics, well-mixed populations are almost always associated with all-to-all interactions; mathematical models are based on complete graphs. In most cases, these models do not predict fixation probabilities in groups of individuals mixed by flows. We propose an analytical description in the fast-flow limit. This approach is valid for processes with global and local selection, and accurately predicts the suppression of selection as competition becomes more local. It provides a modelling tool for biological or social systems with individuals in motion.Comment: 19 pages, 8 figure

Green Plants in the Red: A Baseline Global Assessment for the IUCN Sampled Red List Index for Plants

Plants provide fundamental support systems for life on Earth and are the basis for all terrestrial ecosystems; a decline in plant diversity will be detrimental to all other groups of organisms including humans. Decline in plant diversity has been hard to quantify, due to the huge numbers of known and yet to be discovered species and the lack of an adequate baseline assessment of extinction risk against which to track changes. The biodiversity of many remote parts of the world remains poorly known, and the rate of new assessments of extinction risk for individual plant species approximates the rate at which new plant species are described. Thus the question ‘How threatened are plants?’ is still very difficult to answer accurately. While completing assessments for each species of plant remains a distant prospect, by assessing a randomly selected sample of species the Sampled Red List Index for Plants gives, for the first time, an accurate view of how threatened plants are across the world. It represents the first key phase of ongoing efforts to monitor the status of the world’s plants. More than 20% of plant species assessed are threatened with extinction, and the habitat with the most threatened species is overwhelmingly tropical rain forest, where the greatest threat to plants is anthropogenic habitat conversion, for arable and livestock agriculture, and harvesting of natural resources. Gymnosperms (e.g. conifers and cycads) are the most threatened group, while a third of plant species included in this study have yet to receive an assessment or are so poorly known that we cannot yet ascertain whether they are threatened or not. This study provides a baseline assessment from which trends in the status of plant biodiversity can be measured and periodically reassessed