First Steps towards Underdominant Genetic Transformation of Insect Populations

The idea of introducing genetic modifications into wild populations of insects to stop them from spreading diseases is more than 40 years old. Synthetic disease refractory genes have been successfully generated for mosquito vectors of dengue fever and human malaria. Equally important is the development of population transformation systems to drive and maintain disease refractory genes at high frequency in populations. We demonstrate an underdominant population transformation system in Drosophila melanogaster that has the property of being both spatially self-limiting and reversible to the original genetic state. Both population transformation and its reversal can be largely achieved within as few as 5 generations. The described genetic construct {Ud} is composed of two genes; (1) a UAS-RpL14.dsRNA targeting RNAi to a haploinsufficient gene RpL14 and (2) an RNAi insensitive RpL14 rescue. In this proof-of-principle system the UAS-RpL14.dsRNA knock-down gene is placed under the control of an Actin5c-GAL4 driver located on a different chromosome to the {Ud} insert. This configuration would not be effective in wild populations without incorporating the Actin5c-GAL4 driver as part of the {Ud} construct (or replacing the UAS promoter with an appropriate direct promoter). It is however anticipated that the approach that underlies this underdominant system could potentially be applied to a number of species. Figure

Tumor markers in breast cancer - European Group on Tumor Markers recommendations

Recommendations are presented for the routine clinical use of serum and tissue-based markers in the diagnosis and management of patients with breast cancer. Their low sensitivity and specificity preclude the use of serum markers such as the MUC-1 mucin glycoproteins ( CA 15.3, BR 27.29) and carcinoembryonic antigen in the diagnosis of early breast cancer. However, serial measurement of these markers can result in the early detection of recurrent disease as well as indicate the efficacy of therapy. Of the tissue-based markers, measurement of estrogen and progesterone receptors is mandatory in the selection of patients for treatment with hormone therapy, while HER-2 is essential in selecting patients with advanced breast cancer for treatment with Herceptin ( trastuzumab). Urokinase plasminogen activator and plasminogen activator inhibitor 1 are recently validated prognostic markers for lymph node-negative breast cancer patients and thus may be of value in selecting node-negative patients that do not require adjuvant chemotherapy. Copyright (C) 2005 S. Karger AG, Basel

Confirmation of low genetic diversity and multiple breeding females in a social group of Eurasian badgers from microsatellite and field data

The Eurasian badger ( Meles meles ) is a facultatively social carnivore that shows only rudimentary co-operative behaviour and a poorly defined social hierarchy. Behavioural evidence and limited genetic data have suggested that more than one female may breed in a social group. We combine pregnancy detection by ultrasound and microsatellite locus scores from a well-studied badger population from Wytham Woods, Oxfordshire, UK, to demonstrate that multiple females reproduce within a social group. We found that at least three of seven potential mothers reproduced in a group that contained 11 reproductive age females and nine offspring. Twelve primers showed variability across the species range and only five of these were variable in Wytham. The microsatellites showed a reduced repeat number, a significantly higher number of nonperfect repeats, and moderate heterozygosity levels in Wytham. The high frequency of imperfect repeats and demographic phenomena might be responsible for the reduced levels of variability observed in the badger

Recombination rate and selection strength in HIV intra-patient evolution

The evolutionary dynamics of HIV during the chronic phase of infection is driven by the host immune response and by selective pressures exerted through drug treatment. To understand and model the evolution of HIV quantitatively, the parameters governing genetic diversification and the strength of selection need to be known. While mutation rates can be measured in single replication cycles, the relevant effective recombination rate depends on the probability of coinfection of a cell with more than one virus and can only be inferred from population data. However, most population genetic estimators for recombination rates assume absence of selection and are hence of limited applicability to HIV, since positive and purifying selection are important in HIV evolution. Here, we estimate the rate of recombination and the distribution of selection coefficients from time-resolved sequence data tracking the evolution of HIV within single patients. By examining temporal changes in the genetic composition of the population, we estimate the effective recombination to be r=1.4e-5 recombinations per site and generation. Furthermore, we provide evidence that selection coefficients of at least 15% of the observed non-synonymous polymorphisms exceed 0.8% per generation. These results provide a basis for a more detailed understanding of the evolution of HIV. A particularly interesting case is evolution in response to drug treatment, where recombination can facilitate the rapid acquisition of multiple resistance mutations. With the methods developed here, more precise and more detailed studies will be possible, as soon as data with higher time resolution and greater sample sizes is available.Comment: to appear in PLoS Computational Biolog

Recent Progress in the Use of Glucagon and Glucagon Receptor Antagonists in the Treatment of Diabetes Mellitus

Glucagon is an important pancreatic hormone, released into blood circulation by alpha cells of the islet of Langerhans. Glucagon induces gluconeogenesis and glycogenolysis in hepatocytes, leading to an increase in hepatic glucose production and subsequently hyperglycemia in susceptible individuals. Hyperglucagonemia is a constant feature in patients with T2DM. A number of bioactive agents that can block glucagon receptor have been identified. These glucagon receptor antagonists can reduce the hyperglycemia associated with exogenous glucagon administration in normal as well as diabetic subjects. Glucagon receptor antagonists include isoserine and beta-alanine derivatives, bicyclic 19-residue peptide BI-32169, Des-His1-[Glu9] glucagon amide and related compounds, 5-hydroxyalkyl-4-phenylpyridines, N-[3-cano-6- (1,1 dimethylpropyl)-4,5,6,7-tetrahydro-1-benzothien-2-yl]-2-ethylbutamide, Skyrin and NNC 250926. The absorption, dosage, catabolism, excretion and medicinal chemistry of these agents are the subject of this review. It emphasizes the role of glucagon in glucose homeostasis and how it could be applied as a novel tool for the management of diabetes mellitus by blocking its receptors with either monoclonal antibodies, peptide and non-peptide antagonists or gene knockout techniques

Structural Basis for Allosteric Regulation in the Major Antenna Trimer of Photosystem II

The allosteric regulation of protein function proves important in many life-sustaining processes. In plant photosynthesis, LHCII, the major antenna complex of Photosystem II, employs a delicate switch between light harvesting and photoprotective modes. The switch is triggered by an enlarged pH gradient (ΔpH) across the thylakoid membranes. Using molecular simulations and quantum calculations, we show that ΔpH can tune the light-harvesting potential of the antenna via allosteric regulation of the excitonic coupling in chlorophyll-carotenoid pairs. To this end, we propose how the LHCII excited state lifetime is coupled to the environmental conditions. In line with experimental findings, our theoretical model provides crucial evidence toward the elucidation of the photoprotective switch of higher plants at an all-atom resolution

Regulation of the Mitogen Activated Protein Kinase Kinase (MEK)-1 by NAD-Dependent Deacetylases

Sirtuins are class III deacetylases that regulate many essential processes, including cellular stress, genome stability, and metabolism. Although these NAD+-dependent deacetylases control adaptive cellular responses, identification of sirtuin-regulated signaling targets remain under-studied. Here, we demonstrate that acetylation of the mitogen-activated protein kinase kinase-1 (MEK1) stimulates its kinase activity, and that acetylated MEK1 is under the regulatory control of the sirtuin family members SIRT1 and SIRT2. Treatment of cells with sirtuin inhibitors, or siRNA knockdown of SIRT1 or SIRT2 proteins, increases MEK1 acetylation and subsequent phosphorylation of the extracellular signal-regulated kinase (ERK). Generation of an acetyl-specific MEK1 antibody demonstrates that endogenous acetylated MEK1 is extensively enriched in the nucleus following epidermal growth factor (EGF) stimulation. An acetyl-mimic of MEK1 increases inappropriate growth properties, suggesting that acetylation of MEK1 has oncogenic potential

Prediction of higher mortality reduction for the UK Breast Screening Frequency Trial: A model-based approach on screening intervals

Background: The optimal interval between two consecutive mammograms is uncertain. The UK Frequency Trial did not show a significant difference in breast cancer mortality between screening every year (study group) and screening every 3 years (control group). In this study, the trial is simulated in order to gain insight into the results of the trial and to predict the effect of different screening intervals on breast cancer mortality. Methods: UK incidence, life tables and information from the trial were used in the microsimulation model MISCAN-Fadia to simulate the trial and predict the number of breast ca

Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction.

Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children's social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference); the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a "mental model" of the robot, tailoring the tutoring to the robot's performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot's bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance