Is telomerase reactivation associated with the down-regulatoin of TGFβ receptor-II expression in human breast cancer?

Background Telomerase is a ribonucleoprotein that synthesizes telomeres and plays an important role in chromosomal stability and cellular immortalisation. Telomerase activity is detectable in most human cancers but not in normal somatic cells. TGF beta (transforming growth factor beta) is a member of a family of cytokines that are essential for cell survival and seems to be down-regulated in human cancer. Recent in vitro work using human breast cancer cell lines has suggested that TGF beta down-regulates the expression of hTERT (human telomerase reverse transcriptase) : the catalytic subunit of telomerase. We have therefore hypothesised that telomerase reactivation is associated with reduced immunohisto-chemical expression of TGF beta type II receptor (RII) in human breast cancer. Methods TGF beta RII immunohistochemical expression was determined in 24 infiltrating breast carcinomas with known telomerase activity (17 telomerase-positive and 7 telomerase-negative). Immunohistochemical expression of TGF beta RII was determined by a breast pathologist who was blinded to telomerase data. Results TGF beta RII was detected in all lesions. The percentage of stained cells ranged from 1–100%. The difference in TGF beta RII expression between telomerase positive and negative tumours was not statistically significant (p = 1.0). Conclusion The results of this pilot study suggest that there is no significant association between telomerase reactivation and TGF-beta RII down-regulation in human breast cancer

Factors Influencing the Adoption of Russian Varroa-Resistant Honey Bees

Factors influencing the adoption of Russian Varroa-Resistant honey bees were assessed. Logit results indicate factors associated with the adoption include sales, internet use, and contact with other beekeepers. Negatively associated factors are age and income. Future adoption depends upon previous use and perception.Agribusiness,

What makes or breaks a campaign to stop an invading plant pathogen?

Diseases in humans, animals and plants remain an important challenge in our society. Effective control of invasive pathogens often requires coordinated concerted action of a large group of stakeholders. Both epidemiological and human behavioural factors influence the outcome of a disease control campaign. In mathematical models that are frequently used to guide such campaigns, human behaviour is often ill-represented, if at all. Existing models of human, animal and plant disease that do incorporate participation or compliance are often driven by pay-offs or direct observations of the disease state. It is however very well known that opinion is an important driving factor of human decision making. Here we consider the case study of Citrus Huanglongbing disease (HLB), which is an acute bacterial disease that threatens the sustainability of citrus production across the world. We show how by coupling an epidemiological model of this invasive disease with an opinion dynamics model we are able to answer the question: What makes or breaks the effectiveness of a disease control campaign? Frequent contact between stakeholders and advisors is shown to increase the probability of successful control. More surprisingly, we show that informing stakeholders about the effectiveness of control methods is of much greater importance than prematurely increasing their perceptions of the risk of infection. We discuss the overarching consequences of this finding and the effect on human as well as plant disease epidemics

The second urbanization wave

This report examines the potential for decoupling at the city level. While the majority of the worlds population now live in cities and cities are where most resource consumption takes place, both the pressures and potentials to find ways to reconcile economic growth, wellbeing and the sustainable use of natural resources will therefore be greatest in cities

Online Bayesian phylogenetic inference: Theoretical foundations via sequential Monte Carlo

© 2017 The Author(s). Phylogenetics, the inference of evolutionary trees from molecular sequence data such as DNA, is an enterprise that yields valuable evolutionary understanding of many biological systems. Bayesian phylogenetic algorithms, which approximate a posterior distribution on trees, have become a popular if computationally expensive means of doing phylogenetics. Modern data collection technologies are quickly adding newsequences to already substantial databases.With all current techniques for Bayesian phylogenetics, computation must start anew each time a sequence becomes available, making it costly to maintain an up-to-date estimate of a phylogenetic posterior. These considerations highlight the need for an online Bayesian phylogenetic method which can update an existing posterior with new sequences. Here, we provide theoretical results on the consistency and stability of methods for online Bayesian phylogenetic inference based on Sequential Monte Carlo (SMC) and Markov chain Monte Carlo. We first show a consistency result, demonstrating that the method samples from the correct distribution in the limit of a large number of particles. Next, we derive the first reported set of bounds on how phylogenetic likelihood surfaces change when new sequences are added. These bounds enable us to characterize the theoretical performance of sampling algorithms by bounding the effective sample size (ESS) with a given number of particles from below.We show that the ESS is guaranteed to grow linearly as the number of particles in an SMC sampler grows. Surprisingly, this result holds even though the dimensions of the phylogenetic model grow with each new added sequence

Unified treatment of synchronization patterns in generalized networks with higher-order, multilayer, and temporal interactions

When describing complex interconnected systems, one often has to go beyond the standard network description to account for generalized interactions. Here, we establish a unified framework to simplify the stability analysis of cluster synchronization patterns for a wide range of generalized networks, including hypergraphs, multilayer networks, and temporal networks. The framework is based on finding a simultaneous block diagonalization (SBD) of the matrices encoding the synchronization pattern and the network topology. As an application, we use SBD to discover a novel type of chimera states that only appear in the presence of higher-order interactions. The unified framework established here can be extended to other dynamical processes and can facilitate the discovery of novel emergent phenomena in complex systems with generalized interactions

Autonomous Driving in Highway Scenarios through Artificial Potential Fields and Model Predictive Control

An approach for automated driving in highway scenarios in the context of a two levels hierarchical architecture is proposed. In particular, we define suitable artificial potential functions (APF) combinations that can effectively handle the most relevant maneuvers of highway driving, such as speed and distance tracking, lane keeping, overtaking and returning. Parameters of the APF functions are dynamically tuned according to the acquired scenario. The defined APF are included in the cost function of a Model Predictive Control (MPC) control problem to generate the path trajectory. A behavioral logic described by a finite state machine (FSM), based on sensor acquired data and suitable dynamic conditions is defined to select the most appropriate maneuver to realize. Extensive simulation tests are introduced to show the effectiveness of the proposed approach

Psychological treatments for depression and anxiety in dementia and mild cognitive impairment

BACKGROUND: Experiencing anxiety and depression is very common in people with dementia and mild cognitive impairment (MCI). Psychological interventions have been suggested as a potential treatment for these populations. Current research suggests that people with dementia and MCI have limited opportunities for psychological treatments aimed at improving their well-being. A systematic review of the evidence on their effectiveness is likely to be useful in terms of improving outcomes for patients and for future recommendations for practice. OBJECTIVES: The main objective of this review was to assess the effectiveness of psychological interventions in reducing anxiety and depression in people with dementia or mild cognitive impairment (MCI). SEARCH METHODS: We searched the Cochrane Dementia and Cognitive Improvement Group Specialized Register and additional sources for both published and unpublished data. Selection criteria We included randomised controlled trials (RCTs) comparing a psychological intervention with usual care or a placebo intervention (social contact control) in people with dementia or MCI. DATA COLLECTION AND ANALYSIS: Two review authors worked independently to select trials, extract data and assess studies for risk of bias, using a data extraction form. We contacted authors when further information was not available from the published articles. MAIN RESULTS: Six RCTs involving 439 participants with dementia were included in the review, but no studies of participants with MCI were identified. The studies included people with dementia living in the community or in nursing home care and were carried out in several countries. Only one of the studies was classified as low risk of bias. Five studies were at unclear or high risk of bias due to uncertainties around randomisation, blinding and selective reporting of results. The studies used the different psychological approaches of cognitive behavioural therapy (CBT), interpersonal therapy and counselling. Two studies were of multimodal interventions including a specific psychological therapy. The comparison groups received either usual care, attention-control educational programs, diagnostic feedback or services slightly above usual care. Meta-analysis showed a positive effect of psychological treatments on depression (6 trials, 439 participants, standardised mean difference (SMD) -0.22; 95% confidence interval (CI) -0.41 to -0.03, moderate quality evidence) and on clinician-rated anxiety (2 trials, 65 participants, mean difference (MD) -4.57; 95% CI -7.81 to -1.32, low quality evidence), but not on self-rated anxiety (2 trials, SMD 0.05; 95% CI -0.44 to 0.54) or carer-rated anxiety (1 trial, MD -2.40; 95% CI -4.96 to 0.16). Results were compatible with both benefit and harm on the secondary outcomes of patient quality of life, activities of daily living (ADLs), neuropsychiatric symptoms and cognition, or on carers' self-rated depressive symptoms, but most of the studies did not measure these outcomes. There were no reports of adverse events. AUTHORS' CONCLUSIONS: We found evidence that psychological interventions added to usual care can reduce symptoms of depression and clinician-rated anxiety for people with dementia. We conclude that psychological interventions have the potential to improve patient well-being. Further high quality studies are needed to investigate which treatments are most effective and to evaluate the effect of psychological interventions in people with MCI

Agglomeration during spray drying: Air-borne clusters or breakage at the walls?

Particle agglomeration, wall deposition and resuspension are inherent to many industries and natural processes, and often inter-connected. This work looks into their relation in a confined particle laden swirling flow. It investigates how the size of detergent powder spray dried in a swirl counter-current tower responds to changes in the air flow. Four sets of sprays are investigated under varying combinations of air temperature and velocity that cause the same evaporation. The use of high air velocities accumulates more of the droplets and dry powder in the chamber swirling faster, but it leads to creation of a finer product. Particle-particle and particle-wall contacts are made more frequent and energetic but in turn the swirl troughs the solids to the wall where deposits constantly form and break. Past PIV and tracer studies revealed that the rates of deposition and resuspension are balanced; the data discussed here indicate that the dynamic nature of the deposits is a major contributor to particle formation. In contrast with the usual assumption, the product size seems driven not by inter-particle contacts in airborne state but the ability of the solids to gain kinetic energy and break up a collection of clusters layering on the wall. As a result, the dryer performance becomes driven by the dynamic of deposition and resuspension. This paper studies the efficiency of limiting operation strategies and shows that a low temperature design concept is better suited to control fouling phenomena and improve capacity and energy consumption