1,729 research outputs found

    Luminescence-based complementation assay to assess target engagement and cell permeability of glycolate oxidase (HAO1) inhibitors

    Get PDF
    \ua9 2024 The Authors. Glycolate oxidase (HAO1) catalyses the synthesis of glyoxylate, a common metabolic intermediate that causes renal failure if accumulated. HAO1 inhibition is an emerging treatment for primary hyperoxaluria, a rare disorder of glyoxylate metabolism. Here we report the first cell-based measurement of inhibitor uptake and engagement with HAO1, by adapting the cellular thermal shift assay (CETSA) based on Nano luciferase complementation and luminescence readout. By profiling the interaction between HAO1 and four well-characterised inhibitors in intact and lysed HEK293T cells, we showed that our CETSA method differentiates between low-permeability/high-engagement and high-permeability/low-engagement ligands and is able to rank HAO1 inhibitors in line with both recombinant protein methods and previously reported indirect cellular assays. Our methodology addresses the unmet need for a robust, sensitive, and scalable cellular assay to guide HAO1 inhibitor development and, in broader terms, can be rapidly adapted for other targets to simultaneously monitor compound affinity and cellular permeability

    High-resolution radar measurements of snow avalanches

    Get PDF
    Two snow avalanches that occurred in the winter 2010-2011 at Vallée de la Sionne, Switzerland, are studied using a new phased array FMCW radar system with unprecedented spatial resolution. The 5.3 GHz radar penetrates through the powder cloud and reflects off the underlying denser core. Data are recorded at 50 Hz and have a range resolution better than 1 m over the entire avalanche track. We are able to demonstrate good agreement between the radar results and existing measurement systems that record at particular points on the avalanche track. The radar data reveal a wealth of structure in the avalanche and allow the tracking of individual fronts and surges down the slope for the first time. Key Points Validation between our radar results and existing point measurement systems High-resolution radar allows tracking of fronts and surges from start to finish Velocity linked with topography may be used to measure rheology of snow ©2013. American Geophysical Union. All Rights Reserved

    Impact of Type 2 diabetes prevention programmes based on risk identification and lifestyle intervention intensity strategies: a cost-effectiveness analysis

    Get PDF
    Aim To develop a cost-effectiveness model to compare Type 2 diabetes prevention programmes that target different at-risk population subgroups through lifestyle interventions of varying intensity. Methods An individual patient simulation model simulated the development of diabetes in a representative sample of adults without diabetes from the UK population. The model incorporates trajectories for HbA1c, 2-h glucose, fasting plasma glucose, BMI, systolic blood pressure, total cholesterol and HDL cholesterol. In the model, patients can be diagnosed with diabetes, cardiovascular disease, microvascular complications of diabetes, cancer, osteoarthritis and depression, or can die. The model collects costs and utilities over a lifetime horizon. The perspective is the UK National Health Service and Personal Social Services. We used the model to evaluate the population-wide impact of targeting a lifestyle intervention of varying intensity to six population subgroups defined as at high risk for diabetes. Results The intervention produces 0.0020 to 0.0026 incremental quality-adjusted life-years and saves £15 to £23 per person in the general population, depending on the subgroup targeted. Cost-effectiveness increases with intervention intensity. The most cost-effective options were to target South-Asian people and those with HbA1c levels > 42 mmol/mol (6%). Conclusion The model indicates that diabetes prevention interventions are likely to be cost-saving. The criteria for selecting at-risk individuals differentially has an impact on diabetes and cardiovascular disease outcomes, and on the timing of costs and benefits. The model is not currently able to account for potential differential uptake or efficacy between subgroups. These findings have implications for deciding who should be targeted for diabetes prevention interventions.NIH

    Induction of fibroblast senescence generates a non-fibrogenic myofibroblast phenotype that differentially impacts on cancer prognosis

    Get PDF
    Cancer-associated fibroblasts (CAF) remain a poorly characterized, heterogeneous cell population. Here we characterized two previously described tumor-promoting CAF sub-types, smooth muscle actin (SMA)-positive myofibroblasts and senescent fibroblasts, identifying a novel link between the two

    Looking inside an avalanche using a novel radar system

    Get PDF
    Snow avalanches are a significant natural hazard in alpine regions and their flow dynamics have similarities to pyroclastic flows and other geological mass movements. However, the potential for artificial release and the temporary nature of their deposits makes them somewhat easier to study. This article explains recent developments in radar technology for imaging these flows. These new data mean that, for the first time, we are seeing the whole flow averaged over spatial scales that are dynamically relevant. This provides an opportunity to properly test existing models for the dynamics used in risk applications and to gain knowledge of the flow physics, which will guide the next generation of model formulations

    Evaluation of the current knowledge limitations in breast cancer research: a gap analysis

    Get PDF
    BACKGROUND A gap analysis was conducted to determine which areas of breast cancer research, if targeted by researchers and funding bodies, could produce the greatest impact on patients. METHODS Fifty-six Breast Cancer Campaign grant holders and prominent UK breast cancer researchers participated in a gap analysis of current breast cancer research. Before, during and following the meeting, groups in seven key research areas participated in cycles of presentation, literature review and discussion. Summary papers were prepared by each group and collated into this position paper highlighting the research gaps, with recommendations for action. RESULTS Gaps were identified in all seven themes. General barriers to progress were lack of financial and practical resources, and poor collaboration between disciplines. Critical gaps in each theme included: (1) genetics (knowledge of genetic changes, their effects and interactions); (2) initiation of breast cancer (how developmental signalling pathways cause ductal elongation and branching at the cellular level and influence stem cell dynamics, and how their disruption initiates tumour formation); (3) progression of breast cancer (deciphering the intracellular and extracellular regulators of early progression, tumour growth, angiogenesis and metastasis); (4) therapies and targets (understanding who develops advanced disease); (5) disease markers (incorporating intelligent trial design into all studies to ensure new treatments are tested in patient groups stratified using biomarkers); (6) prevention (strategies to prevent oestrogen-receptor negative tumours and the long-term effects of chemoprevention for oestrogen-receptor positive tumours); (7) psychosocial aspects of cancer (the use of appropriate psychosocial interventions, and the personal impact of all stages of the disease among patients from a range of ethnic and demographic backgrounds). CONCLUSION Through recommendations to address these gaps with future research, the long-term benefits to patients will include: better estimation of risk in families with breast cancer and strategies to reduce risk; better prediction of drug response and patient prognosis; improved tailoring of treatments to patient subgroups and development of new therapeutic approaches; earlier initiation of treatment; more effective use of resources for screening populations; and an enhanced experience for people with or at risk of breast cancer and their families. The challenge to funding bodies and researchers in all disciplines is to focus on these gaps and to drive advances in knowledge into improvements in patient care

    Parts verification for multi-level-dependent demand manufacturing systems: a recognition and classification structure

    Get PDF
    This research has developed and implemented a part recognition and classification structure to execute parts verification in a multi-level dependent demand manufacturing system. The part recognition algorithm enables the parent and child relationship between parts to be recognised in a finite-capacitated manufacturing system. This algorithm was developed using SIMAN simulation language and implemented in a multi-level dependent demand manufacturing simulation model. The part classification structure enables the modelling of a multi-level dependent demand manufacturing between parts to be carried out effectively. The part classification structure was programmed using Visual Basic Application (VBA) and was integrated to the work-to-list generated from a simulated MRP model. This part classification structure was then implemented in the multi-level dependent demand manufacturing simulation model. Two stages of implementation, namely parameterisation and execution, of the part recognition and classification structure were carried out. A real case study was used and five detail steps of execution were processed. Simulation experiments and MRP were run to verify and validate the part recognition and classification structure. The results led to the conclusion that implementation of the recognition and classification structure has effectively verified the correct parts and sub-assemblies used for the correct product and order. No parts and sub-assemblies shortages were found, and the quantity required was produced. The scheduled release for some orders was delayed due to overload of the required resources. When the loading is normal, all scheduled release timing is adhered to. The recognition and classification structure has a robust design; hence it can be easily adapted to new systems parameter to study a different or more complex case

    Kinase/phosphatase overexpression reveals pathways regulating hippocampal neuron morphology

    Get PDF
    Kinases and phosphatases that regulate neurite number versus branching versus extension are weakly correlated.The kinase family that most strongly enhances neurite growth is a family of non-protein kinases; sugar kinases related to NADK.Pathway analysis revealed that genes in several cancer pathways were highly active in enhancing neurite growth

    Joint IARC/NCI International Cancer Seminar Series Report: Expert consensus on future directions for ovarian carcinoma research

    Get PDF
    Recently, ovarian cancer research has evolved considerably because of the emerging recognition that rather than a single disease, ovarian carcinomas comprise several different histotypes that vary by etiologic origin, risk factors, molecular profiles, therapeutic approaches, and clinical outcome. Despite significant progress in our understanding of the etiologic heterogeneity of ovarian cancer, as well as important clinical advances, it remains the eighth most frequently diagnosed cancer in women worldwide and the most fatal gynecologic cancer. The International Agency for Research on Cancer (IARC) and the US National Cancer Institute (NCI) jointly convened an expert panel on ovarian carcinoma to develop consensus research priorities based on evolving scientific discoveries. Expertise ranged from etiology, prevention, early detection, pathology, model systems, molecular characterization, and treatment/clinical management. This report summarizes the current state of knowledge and highlights expert consensus on future directions to continue advancing etiologic, epidemiologic, and prognostic research on ovarian carcinoma
    corecore