University of Nottingham

About: University of Nottingham is a education organization based out in Nottingham, Nottingham, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 54772 authors who have published 119600 publications receiving 4227408 citations. The organization is also known as: The University of Nottingham & University College, Nottingham.

Comparison of calibration methods for atomic-force microscopy cantilevers

Abstract: Th es cientific community needs a rapid and reliable way of accurately determining the stiffness of atomic-force microscopy cantilevers. We have compared the experimentally determined values of stiffness for ten cantilever probes using four different methods. For rectangular silicon cantilever beams of well defined geometry, the approaches all yield values within 17% of the manufacturer’s nominal stiffness. One of the methods is new, based on the acquisition and analysis of thermal distribution functions of the oscillator’s amplitude fluctuations. We evaluate this method in comparison to the three others and recommend it for its ease of use and broad applicability.

Unikernels: library operating systems for the cloud

Abstract: We present unikernels, a new approach to deploying cloud services via applications written in high-level source code. Unikernels are single-purpose appliances that are compile-time specialised into standalone kernels, and sealed against modification when deployed to a cloud platform. In return they offer significant reduction in image sizes, improved efficiency and security, and should reduce operational costs. Our Mirage prototype compiles OCaml code into unikernels that run on commodity clouds and offer an order of magnitude reduction in code size without significant performance penalty. The architecture combines static type-safety with a single address-space layout that can be made immutable via a hypervisor extension. Mirage contributes a suite of type-safe protocol libraries, and our results demonstrate that the hypervisor is a platform that overcomes the hardware compatibility issues that have made past library operating systems impractical to deploy in the real-world.

Effectiveness of home exercise on pain and disability from osteoarthritis of the knee: a randomised controlled trial

Abstract: Objective—To assess the eVect of a home based exercise programme, designed to improve quadriceps strength, on knee pain and disability. Methods—191 men and women with knee pain aged 40‐80 were recruited from the community and randomised to exercise (n=113) or no intervention (n=78). The exercise group performed strengthening exercises daily for six months. The primary outcome measure was change in knee pain (Western Ontario McMaster Osteoarthritis index (WOMAC)). Secondary measures included visual analogue scales (VAS) for pain on stairs and walking and WOMAC physical function scores. Results—WOMAC pain score reduced by 22.5% in the exercise group and by 6.2% in the control group (between group diVerence p<0.05, unpaired t test).VAS scores for pain also reduced in the exercise group compared with the control group (p<0.05). Physical function scores reduced by 17.4% in the exercise group and were unchanged in controls (p<0.05). Conclusion—A simple programme of home quadriceps exercises can significantly improve self reported knee pain and function. (Ann Rheum Dis 1999;58:15‐19)

An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer

Abstract: Estrogen receptor (ER)-negative breast cancer specimens are predominantly of high grade, have frequent p53 mutations, and are broadly divided into HER2-positive and basal subtypes. Although ER-negative disease has overall worse prognosis than does ER-positive breast cancer, not all ER-negative breast cancer patients have poor clinical outcome. Reliable identification of ER-negative tumors that have a good prognosis is not yet possible. We apply a recently proposed feature selection method in an integrative analysis of three major microarray expression datasets to identify molecular subclasses and prognostic markers in ER-negative breast cancer. We find a subclass of basal tumors, characterized by over-expression of immune response genes, which has a better prognosis than the rest of ER-negative breast cancers. Moreover, we show that, in contrast to ER-positive tumours, the majority of prognostic markers in ER-negative breast cancer are over-expressed in the good prognosis group and are associated with activation of complement and immune response pathways. Specifically, we identify an immune response related seven-gene module and show that downregulation of this module confers greater risk for distant metastasis (hazard ratio 2.02, 95% confidence interval 1.2-3.4; P = 0.009), independent of lymph node status and lymphocytic infiltration. Furthermore, we validate the immune response module using two additional independent datasets. We show that ER-negative basal breast cancer is a heterogeneous disease with at least four main subtypes. Furthermore, we show that the heterogeneity in clinical outcome of ER-negative breast cancer is related to the variability in expression levels of complement and immune response pathway genes, independent of lymphocytic infiltration.