Identification of RBCK1 as a novel regulator of FKBPL: implications for tumor growth and response to tamoxifen

FKBPL has been implicated in processes associated with cancer, including regulation of tumor growth and angiogenesis with high levels of FKBPL prognosticating for improved patient survival. Understanding how FKBPL levels are controlled within the cell is therefore critical. We have identifed a novel role for RBCK1 as an FKBPL-interacting protein, which regulates FKBPL stability at the post-translational level via ubiquitination. Both RBCK1 and FKBPL are upregulated by 17-b-estradiol and interact within heat shock protein 90 chaperone complexes, together with estrogen receptor-a (ERa). Furthermore, FKBPL and RBCK1 associate with ERa at the promoter of the estrogen responsive gene, pS2, and regulate pS2 levels. MCF-7 clones stably overexpressing RBCK1 were shown to have reduced proliferation and increased levels of FKBPL and p21. Furthermore, these clones were resistant to tamoxifen therapy, suggesting that RBCK1 could be a predictive marker of response to endocrine therapy. RBCK1 knockdown using targeted small interfering RNA resulted in increased proliferation and increased sensitivity to tamoxifen treatment. Moreover, in support of our in vitro data, analysis of mRNA microarray data sets demonstrated that high levels of FKBPL and RBCK1 correlated with increased patient survival, whereas high RBCK1 predicted for a poor response to tamoxifen. Our findings support a role for RBCK1 in the regulation of FKBPL with important implications for estrogen receptor signaling, cell proliferation and response to endocrine therapy.

An Arabidopsis mutant cex1 exhibits constant accumulation of jasmonate-regulated AtVSP, Thi2.1 and PDF1.2.

Jasmonates (JA) act as a regulator in plant growth as well as a signal in plant defense. The Arabidopsis vegetative storage protein (AtVSP) and plant defense-related proteins thionin (Thi2.1) and defensin (PDF1.2) have previously been shown to accumulate in response to JA induction. In this report, we isolated and characterized a novel recessive mutant, cex1, conferring constitutive JA-responsive phenotypes including JA-inhibitory growth and constitutive expression of JA-regulated AtVSP, Thi2.1 and PDF1.2. The plant morphology and the gene expression pattern of the cex1 mutant could be phenocopied by treatment of wild-type plants with exogenous JA, indicating that CEX1 might be a negative regulator of the JA response pathway.

The Forgiving Graph: a distributed data structure for low stretch under adversarial attack

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick “repairs,” which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions, without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been l in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most l log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degree would have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network.

Nile blue-based nano-sized pH sensors for simultaneous far-red and near-infrared live bioimaging

Diblock copolymer vesicles are tagged with pH-responsive Nile Blue-based labels and used as a new type of pH-responsive colorimetric/fluorescent biosensor for far-red and near-infrared imaging of live cells. The diblock copolymer vesicles described herein are based on poly(2-(methacryloyloxy)ethyl phosphorylcholine-block-2-(diisopropylamino)ethyl methacrylate) [PMPC-PDPA]: the biomimetic PMPC block is known to facilitate rapid cell uptake for a wide range of cell lines, while the PDPA block constitutes the pH-responsive component that enables facile vesicle self-assembly in aqueous solution. These biocompatible vesicles can be utilized to detect interstitial hypoxic/acidic regions in a tumor model via a pH-dependent colorimetric shift. In addition, they are also useful for selective intracellular staining of lysosomes and early endosomes via subtle changes in fluorescence emission. Such nanoparticles combine efficient cellular uptake with a pH-responsive Nile Blue dye label to produce a highly versatile dual capability probe. This is in marked contrast to small molecule dyes, which are usually poorly uptaken by cells, frequently exhibit cytotoxicity, and are characterized by intracellular distributions invariably dictated by their hydrophilic/hydrophobic balance.

Environmental Challenges and Physiological Solutions: Comparative Energetic Daily Rhythms of Field Mice Populations from Different Ecosystems

Daily and seasonal variations in physiological characteristics of mammals can be considered adaptations to temporal habitat variables. Across different ecosystems, physiological adjustments are expected to be sensitive to different environmental signals such as changes in photoperiod, temperature or water and food availability; the relative importance of a particular signal being dependent on the ecosystem in question. Energy intake, oxygen consumption (VO) and body temperature (T) daily rhythms were compared between two populations of the broad-toothed field mouse Apodemus mystacinus, one from a Mediterranean and another from a sub-Alpine ecosystem. Mice were acclimated to short-day (SD) 'winter' and long-day (LD) 'summer' photoperiods under different levels of salinity simulating osmotic challenges. Mediterranean mice had higher VO values than sub-Alpine mice. In addition, mice exposed to short days had higher VO values when given water with a high salinity compared with mice exposed to long days. By comparison, across both populations, increasing salinity resulted in a decreased T in SD- but not in LD-mice. Thus, SD-mice may conserve energy by decreasing T during ('winter') conditions which are expected to be cool, whereas LD-mice might do the opposite and maintain a higher T during ('summer') conditions which are expected to be warm. LD-mice behaved to reduce energy expenditure, which might be considered a useful trait during 'summer' conditions. Overall, increasing salinity was a clear signal for Mediterranean-mice with resultant effects on VO and T daily rhythms but had less of an effect on sub-Alpine mice, which were more responsive to changes in photoperiod. Results provide an insight into how different populations respond physiologically to various environmental challenges.

Edge-preserving self-healing: Keeping network backbones densely connected

Healing algorithms play a crucial part in distributed peer-to-peer networks where failures occur continuously and frequently. Whereas there are approaches for robustness that rely largely on built-in redundancy, we adopt a responsive approach that is more akin to that of biological networks e.g. the brain. The general goal of self-healing distributed graphs is to maintain certain network properties while recovering from failure quickly and making bounded alterations locally. Several self-healing algorithms have been suggested in the recent literature [IPDPS'08, PODC'08, PODC'09, PODC'11]; they heal various network properties while fulfilling competing requirements such as having low degree increase while maintaining connectivity, expansion and low stretch of the network. In this work, we augment the previous algorithms by adding the notion of edge-preserving self-healing which requires the healing algorithm to not delete any edges originally present or adversarialy inserted. This reflects the cost of adding additional edges but more importantly it immediately follows that edge preservation helps maintain any subgraph induced property that is monotonic, in particular important properties such as graph and subgraph densities. Density is an important network property and in certain distributed networks, maintaining it preserves high connectivity among certain subgraphs and backbones. We introduce a general model of self-healing, and introduce xheal+, an edge-preserving version of xheal[PODC'11]. © 2012 IEEE.

The forgiving tree: a self-healing distributed data structure

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that the following process continues for up to n rounds where n is the total number of nodes initially in the network: the adversary deletesan arbitrary node from the network, then the network responds by quickly adding a small number of new edges.

We present a distributed data structure that ensures two key properties. First, the diameter of the network is never more than O(log Delta) times its original diameter, where Delta is the maximum degree of the network initially. We note that for many peer-to-peer systems, Delta is polylogarithmic, so the diameter increase would be a O(loglog n) multiplicative factor. Second, the degree of any node never increases by more than 3 over its original degree. Our data structure is fully distributed, has O(1) latency per round and requires each node to send and receive O(1) messages per round. The data structure requires an initial setup phase that has latency equal to the diameter of the original network, and requires, with high probability, each node v to send O(log n) messages along every edge incident to v. Our approach is orthogonal and complementary to traditional topology-based approaches to defending against attack.

From survey to policy: community relations in Northern Ireland

Public policy is expected to be both responsive to societal views and accountable to all citizens. As such, policy is informed, but not governed, by public opinion. Therefore, understanding the attitudes of the public is important, both to help shape and to evaluate policy priorities. In this way, surveys play a potentially important role in the policy making process.

The aim of this paper is to explore the role of survey research in policy making in Northern Ireland, with particular reference to community relations (better known internationally as good relations). In a region which is emerging from 40 years of conflict, community relations is a key policy area.

For more than 20 years, public attitudes to community relations have been recorded and monitored using two key surveys: the Northern Ireland Social Attitudes Survey (1989 to 1996) and the Northern Ireland Life and Times Survey (1998 to present). This paper will illustrate how these important time series datasets have been used to both inform and evaluate government policy in relation to community relations. By using four examples, we will highlight how these survey data have provided key government indicators of community relations, as well as how they have been used by other groups (such as NGOs) within policy consultation debates. Thus, the paper will provide a worked example of the integral, and bi-directional relationship between attitude measurement and policy making.

Causal Models of Clinically Significant Behaviors in Angelman, Cornelia de Lange, Prader-Willi and Smith-Magenis Syndromes

The operant learning theory account of behaviors of clinical significance in people with intellectual disability (ID) has dominated the field for nearly 50 years. However, in the last two decades, there has been a substantial increase in published research that describes the behavioral phenotypes of genetic disorders and shows that behaviors such as self-injury and aggression are more common in some syndromes than might be expected given group characteristics. These cross-syndrome differences in prevalence warrant explanation, not least because this observation challenges an exclusively operant learning theory account. To explore this possible conflict between theoretical account and empirical observation, we describe the genetic cause and physical, social, cognitive and behavioral phenotypes of four disorders associated with ID (Angleman, Cornelia de Lange, Prader-Willi and Smith-Magenis syndromes) and focus on the behaviors of clinical significance in each syndrome. For each syndrome we then describe a model of the interactions between physical characteristics, cognitive and motivational endophenotypes and environmental factors (including operant reinforcement) to account for the resultant behavioral phenotype. In each syndrome it is possible to identify pathways from gene to physical phenotype to cognitive or motivational endophenotype to behavior to environment and back to behavior. We identify the implications of these models for responsive and early intervention and the challenges for research in this area. We identify a pressing need for meaningful dialog between different disciplines to construct better informed models that can incorporate all relevant and robust empirical evidence.

Managing grid computations: An ORC-based approach

In this paper a model of grid computation that supports both heterogeneity and dynamicity is presented. The model presupposes that user sites contain software components awaiting execution on the grid. User sites and grid sites interact by means of managers which control dynamic behaviour. The orchestration language ORC [9,10] offers an abstract means of specifying operations for resource acquisition and execution monitoring while allowing for the possibility of non-responsive hardware. It is demonstrated that ORC is sufficiently expressive to model typical kinds of grid interactions.

Enforcing Employment Discrimination Law - Potential Transplants from Italy to Britain and Vice Versa?

While substantive EU non-discrimination law has been harmonized in great detail, the enforcement regime for EU non-discrimination law consists merely of a few isolated elements. Thus, the pursuit of unity through harmonization in substantive EU law is accompanied by considerable regulatory autonomy for Member States in securing the efficiency of those laws, reflecting the diversity of national enforcement regimes, and resulting in twenty-seven different national models for enforcing discrimination law in labour markets. This article pursues two connected arguments through a comparison of rules for enforcing non-discrimination law in labour markets in Britain and Italy. First, it argues that enforcing non-discrimination law in labour markets is best achieved when responsive governance, repressive regulation and mainstreaming equality law are combined. Second, the article submits that diversity of national legal orders within the EU is not necessarily detrimental, as it offers opportunities for mutual learning across legal systems.The notion of mutual learning across systems is proposed in order to analyse the transnational migration of legal ideas within the EU. Such migration has been criticized in debates about the ‘transplantation’ of legal concepts or legal irritation through foreign legal ideas, in particular by comparative labour lawyers. However, EU harmonization policies in the field of non-discrimination law aim to impact on national labour laws. The article develops the notion of mutual learning across legal systems in order to establish conditions for transnational migration of legal ideas, and demonstrates the viability of these concepts by applying them to the field of non-discrimination law

Pitfalls in Protection: How Theory Can Enrich Our Understanding of Regulatory Compliance Problems in Planning Practice

This paper responds to demands for greater academic investigation into environmental protection, specifically the practical and structural problems which underpin regulatory compliance in the planning system. It critiques traditional theories of regulation and answers calls for the development of a thematic lens to facilitate the scrutiny of not only operational practice, but also the broader institutional regime. An empirical investigation builds upon the construct of really responsive regulation to study planning control and it becomes apparent that not only are there significant procedural planning difficulties facing regulatory compliance, but also that a much wider raft of issues must be considered if the complex equation is to be solved. The findings demonstrate how theory can be applied to enrich our rudimentary understanding of deep-seated problems and foster insights into areas of structural importance which are relevant to both planning and the wider regulatory arena.

Effects of a demand-led evidence briefing service on the uptake and use of research evidence by commissioners of health services: protocol for a controlled before and after study

Background: Clinical Commissioning Groups (CCGs) are mandated to use research evidence effectively to ensure optimum use of resources by the National Health Service (NHS), both in accelerating innovation and in stopping the use of less effective practices and models of service delivery. We intend to evaluate whether access to a demand-led evidence service improves uptake and use of research evidence by NHS commissioners compared with less intensive and less targeted alternatives. 

Methods/design: This is a controlled before and after study involving CCGs in the North of England. Participating CCGs will receive one of three interventions to support the use of research evidence in their decision-making:1) consulting plus responsive push of tailored evidence; 2) consulting plus an unsolicited push of non-tailored evidence; or 3) standard service unsolicited push of non-tailored evidence. Our primary outcome will be changed at 12 months from baseline of a CCGs ability to acquire, assess, adapt and apply research evidence to support decision-making. Secondary outcomes will measure individual clinical leads and managers’ intentions to use research evidence in decision making. Documentary evidence of the use of the outputs of the service will be sought. A process evaluation will evaluate the nature and success of the interactions both within the sites and between commissioners and researchers delivering the service. 

Discussion: The proposed research will generate new knowledge of direct relevance and value to the NHS. The findings will help to clarify which elements of the service are of value in promoting the use of research evidence.Those involved in NHS commissioning will be able to use the results to inform how best to build the infrastructure they need to acquire, assess, adapt and apply research evidence to support decision-making and to fulfil their statutory duties under the Health and Social Care Act.

Biotransformation of zearalenone and zearalenols to their major glucuronide metabolites reduces estrogenic activity

Zearalenone (ZEN) is a mycotoxin produced by Fusarium fungi. Once ingested, ZEN may be absorbed andmetabolised to a- and b-zearalenol (a-ZOL, b-ZOL), and to a lesser extent a- and b-zearalanol (a-ZAL,b-ZAL). Further biotransformation to glucuronide conjugates also occurs to facilitate the elimination ofthese toxins from the body. Unlike ZEN and its metabolites, information regarding the estrogenic activityof these glucuronide conjugates in various tissues is lacking. ZEN-14-O-glucuronide, a-ZOL-14-O-glucuronide,a-ZOL-7-O-glucuronide, b-ZOL-14-O-glucuronide and b-ZOL-16-O-glucuronide, previouslyobtained as the major products from preparative enzymatic synthesis, were investigated for their potentialto cause endocrine disruption through interference with estrogen receptor transcriptional activity.All five glucuronide conjugates showed a very weak agonist response in an estrogen responsive reportergene assay (RGA), with activity ranging from 0.0001% to 0.01% of that of 17b-estradiol, and also lessthan that of ZEN, a-ZOL and b-ZOL which have previously shown estrogenic potencies of the order 17bestradiol> a-ZOL > ZEN > b-ZOL. Confirmatory mass spectrometry revealed that any activity observedwas likely a result of minor deconjugation of the glucuronide moiety. This study confirms that formationof ZEN and ZOL glucuronides is a detoxification reaction with regard to estrogenicity, serving as a potentialhost defence mechanism against ZEN-induced estrogenic activity.

Overexpression of the microRNA miR-433 promotes resistance to paclitaxel through the induction of cellular senescence in ovarian cancer cells

Annually, ovarian cancer (OC) affects 240,000 women worldwide and is the most lethal gynecological malignancy. High-grade serous OC (HGSOC) is the most common and aggressive OC subtype, characterized by widespread genome changes and chromosomal instability and is consequently poorly responsive to chemotherapy treatment. The objective of this study was to investigate the role of the microRNA miR-433 in the cellular response of OC cells to paclitaxel treatment. We show that stable miR-433 expression in A2780 OC cells results in the induction of cellular senescence demonstrated by morphological changes, downregulation of phosphorylated retinoblastoma (p-Rb), and an increase in β-galactosidase activity. Furthermore, in silico analysis identified four possible miR-433 target genes associated with cellular senescence: cyclin-dependent kinase 6 (CDK6), MAPK14, E2F3, and CDKN2A. Mechanistically, we demonstrate that downregulation of p-Rb is attributable to a miR-433-dependent downregulation of CDK6, establishing it as a novel miR-433 associated gene. Interestingly, we show that high miR-433 expressing cells release miR-433 into the growth media via exosomes which in turn can induce a senescence bystander effect. Furthermore, in relation to a chemotherapeutic response, quantitative real-time polymerase chain reaction (qRT-PCR) analysis revealed that only PEO1 and PEO4 OC cells with the highest miR-433 expression survive paclitaxel treatment. Our data highlight how the aberrant expression of miR-433 can adversely affect intracellular signaling to mediate chemoresistance in OC cells by driving cellular senescence.