Duality Invariant Actions and Generalised Geometry

We construct the non-linear realisation of the semi-direct product of E(11) and its first fundamental representation at lowest order and appropriate to spacetime dimensions four to seven. This leads to a non-linear realisation of the duality groups and introduces fields that depend on a generalised space which possess a generalised vielbein. We focus on the part of the generalised space on which the duality groups alone act and construct an invariant action.Comment: 59 pages (typos fixed and added comments

Computing the common zeros of two bivariate functions via Bézout resultants

The common zeros of two bivariate functions can be computed by finding the common zeros of their polynomial interpolants expressed in a tensor Chebyshev basis. From here we develop a bivariate rootfinding algorithm based on the hidden variable resultant method and Bézout matrices with polynomial entries. Using techniques including domain subdivision, Bézoutian regularization, and local refinement we are able to reliably and accurately compute the simple common zeros of two smooth functions with polynomial interpolants of very high degree (≥ 1000). We analyze the resultant method and its conditioning by noting that the Bézout matrices are matrix polynomials. Two implementations are available: one on the Matlab Central File Exchange and another in the roots command in Chebfun2 that is adapted to suit Chebfun’s methodology

Creatine Monohydrate and Conjugated Linoleic Acid Improve Strength and Body Composition Following Resistance Exercise in Older Adults

Aging is associated with lower muscle mass and an increase in body fat. We examined whether creatine monohydrate (CrM) and conjugated linoleic acid (CLA) could enhance strength gains and improve body composition (i.e., increase fat-free mass (FFM); decrease body fat) following resistance exercise training in older adults (>65 y). Men (N = 19) and women (N = 20) completed six months of resistance exercise training with CrM (5g/d)+CLA (6g/d) or placebo with randomized, double blind, allocation. Outcomes included: strength and muscular endurance, functional tasks, body composition (DEXA scan), blood tests (lipids, liver function, CK, glucose, systemic inflammation markers (IL-6, C-reactive protein)), urinary markers of compliance (creatine/creatinine), oxidative stress (8-OH-2dG, 8-isoP) and bone resorption (Ν-telopeptides). Exercise training improved all measurements of functional capacity (P<0.05) and strength (P<0.001), with greater improvement for the CrM+CLA group in most measurements of muscular endurance, isokinetic knee extension strength, FFM, and lower fat mass (P<0.05). Plasma creatinine (P<0.05), but not creatinine clearance, increased for CrM+CLA, with no changes in serum CK activity or liver function tests. Together, this data confirms that supervised resistance exercise training is safe and effective for increasing strength in older adults and that a combination of CrM and CLA can enhance some of the beneficial effects of training over a six-month period. Trial Registration. ClinicalTrials.gov NCT0047390

Bone Marrow Stromal Cells Modulate Mouse ENT1 Activity and Protect Leukemia Cells from Cytarabine Induced Apoptosis

BACKGROUND: Despite a high response rate to chemotherapy, the majority of patients with acute myeloid leukemia (AML) are destined to relapse due to residual disease in the bone marrow (BM). The tumor microenvironment is increasingly being recognized as a critical factor in mediating cancer cell survival and drug resistance. In this study, we propose to identify mechanisms involved in the chemoprotection conferred by the BM stroma to leukemia cells. METHODS: Using a leukemia mouse model and a human leukemia cell line, we studied the interaction of leukemia cells with the BM microenvironment. We evaluated in vivo and in vitro leukemia cell chemoprotection to different cytotoxic agents mediated by the BM stroma. Leukemia cell apoptosis was assessed by flow cytometry and western blotting. The activity of the equilibrative nucleoside transporter 1 (ENT1), responsible for cytarabine cell incorporation, was investigated by measuring transport and intracellular accumulation of (3)H-adenosine. RESULTS: Leukemia cell mobilization from the bone marrow into peripheral blood in vivo using a CXCR4 inhibitor induced chemo-sensitization of leukemia cells to cytarabine, which translated into a prolonged survival advantage in our mouse leukemia model. In vitro, the BM stromal cells secreted a soluble factor that mediated significant chemoprotection to leukemia cells from cytarabine induced apoptosis. Furthermore, the BM stromal cell supernatant induced a 50% reduction of the ENT1 activity in leukemia cells, reducing the incorporation of cytarabine. No protection was observed when radiation or other cytotoxic agents such as etoposide, cisplatin and 5-fluorouracil were used. CONCLUSION: The BM stroma secretes a soluble factor that significantly protects leukemia cells from cytarabine-induced apoptosis and blocks ENT1 activity. Strategies that modify the chemo-protective effects mediated by the BM microenvironment may enhance the benefit of conventional chemotherapy for patients with AML

Application of 3D Zernike descriptors to shape-based ligand similarity searching

Background: The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. Results: In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability

New insights into the synergism of nucleoside analogs with radiotherapy

Nucleoside analogs have been frequently used in combination with radiotherapy in the clinical setting, as it has long been understood that inhibition of DNA repair pathways is an important means by which many nucleoside analogs synergize. Recent advances in our understanding of the structure and function of deoxycytidine kinase (dCK), a critical enzyme required for the anti-tumor activity for many nucleoside analogs, have clarified the mechanistic role this kinase plays in chemo- and radio-sensitization. A heretofore unrecognized role of dCK in the DNA damage response and cell cycle machinery has helped explain the synergistic effect of these agents with radiotherapy. Since most currently employed nucleoside analogs are primarily activated by dCK, these findings lend fresh impetus to efforts focused on profiling and modulating dCK expression and activity in tumors. In this review we will briefly review the pharmacology and biochemistry of the major nucleoside analogs in clinical use that are activated by dCK. This will be followed by discussions of recent advances in our understanding of dCK activation via post-translational modifications in response to radiation and current strategies aimed at enhancing this activity in cancer cells

Multidimensional individualised Physical ACTivity (Mi-PACT) - a technology-enabled intervention to promote physical activity in primary care: Study protocol for a randomised controlled trial

© 2015 Peacock et al. Background: Low physical activity is a major public health problem. New cost-effective approaches that stimulate meaningful long-term changes in physical activity are required, especially within primary care settings. It is becoming clear that there are various dimensions to physical activity with independent health benefits. Advances in technology mean that it is now possible to generate multidimensional physical activity 'profiles' that provide a more complete representation of physical activity and offer a variety of options that can be tailored to the individual. Mi-PACT is a randomised controlled trial designed to examine whether personalised multidimensional physical activity feedback and self-monitoring alongside trainer-supportive sessions increases physical activity and improves health outcomes in at-risk men and women. Methods/Design: We aim to recruit 216 patients from within primary care aged 40 to 70years and at medium or high risk of cardiovascular disease and/or type II diabetes mellitus. Adopting an unequal allocation ratio (intervention: control) of 2:1, participants will be randomised to one of two groups, usual care or the intervention. The control group will receive usual care from their general practitioner (GP) and standardised messages about physical activity for health. The intervention group will receive physical activity monitors and access to a web-based platform for a 3-month period to enable self-monitoring and the provision of personalised feedback regarding the multidimensional nature of physical activity. In addition, this technology-enabled feedback will be discussed with participants on 5 occasions during supportive one-to-one coaching sessions across the 3-month intervention. The primary outcome measure is physical activity, which will be directly assessed using activity monitors for a 7-day period at baseline, post intervention and at 12months. Secondary measures (at these time-points) include weight loss, fat mass, and markers of metabolic control, motivation and well-being. Discussion: Results from this study will provide insight into the effects of integrated physical activity profiling and self-monitoring combined with in-person support on physical activity and health outcomes in patients at risk of future chronic disease. Trial registration:ISRCTN18008011Trial registration date: 31 July 201

Towards a Physiology-Based Measure of Pain: Patterns of Human Brain Activity Distinguish Painful from Non-Painful Thermal Stimulation

Pain often exists in the absence of observable injury; therefore, the gold standard for pain assessment has long been self-report. Because the inability to verbally communicate can prevent effective pain management, research efforts have focused on the development of a tool that accurately assesses pain without depending on self-report. Those previous efforts have not proven successful at substituting self-report with a clinically valid, physiology-based measure of pain. Recent neuroimaging data suggest that functional magnetic resonance imaging (fMRI) and support vector machine (SVM) learning can be jointly used to accurately assess cognitive states. Therefore, we hypothesized that an SVM trained on fMRI data can assess pain in the absence of self-report. In fMRI experiments, 24 individuals were presented painful and nonpainful thermal stimuli. Using eight individuals, we trained a linear SVM to distinguish these stimuli using whole-brain patterns of activity. We assessed the performance of this trained SVM model by testing it on 16 individuals whose data were not used for training. The whole-brain SVM was 81% accurate at distinguishing painful from non-painful stimuli (p<0.0000001). Using distance from the SVM hyperplane as a confidence measure, accuracy was further increased to 84%, albeit at the expense of excluding 15% of the stimuli that were the most difficult to classify. Overall performance of the SVM was primarily affected by activity in pain-processing regions of the brain including the primary somatosensory cortex, secondary somatosensory cortex, insular cortex, primary motor cortex, and cingulate cortex. Region of interest (ROI) analyses revealed that whole-brain patterns of activity led to more accurate classification than localized activity from individual brain regions. Our findings demonstrate that fMRI with SVM learning can assess pain without requiring any communication from the person being tested. We outline tasks that should be completed to advance this approach toward use in clinical settings