772 research outputs found

    Short-term efficacy of physical interventions in osteoarthritic knee pain. A systematic review and meta-analysis of randomised placebo-controlled trials.

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    BACKGROUND: Treatment efficacy of physical agents in osteoarthritis of the knee (OAK) pain has been largely unknown, and this systematic review was aimed at assessing their short-term efficacies for pain relief. METHODS: Systematic review with meta-analysis of efficacy within 1-4 weeks and at follow up at 1-12 weeks after the end of treatment. RESULTS: 36 randomised placebo-controlled trials (RCTs) were identified with 2434 patients where 1391 patients received active treatment. 33 trials satisfied three or more out of five methodological criteria (Jadad scale). The patient sample had a mean age of 65.1 years and mean baseline pain of 62.9 mm on a 100 mm visual analogue scale (VAS). Within 4 weeks of the commencement of treatment manual acupuncture, static magnets and ultrasound therapies did not offer statistically significant short-term pain relief over placebo. Pulsed electromagnetic fields offered a small reduction in pain of 6.9 mm [95% CI: 2.2 to 11.6] (n = 487). Transcutaneous electrical nerve stimulation (TENS, including interferential currents), electro-acupuncture (EA) and low level laser therapy (LLLT) offered clinically relevant pain relieving effects of 18.8 mm [95% CI: 9.6 to 28.1] (n = 414), 21.9 mm [95% CI: 17.3 to 26.5] (n = 73) and 17.7 mm [95% CI: 8.1 to 27.3] (n = 343) on VAS respectively versus placebo control. In a subgroup analysis of trials with assumed optimal doses, short-term efficacy increased to 22.2 mm [95% CI: 18.1 to 26.3] for TENS, and 24.2 mm [95% CI: 17.3 to 31.3] for LLLT on VAS. Follow-up data up to 12 weeks were sparse, but positive effects seemed to persist for at least 4 weeks after the course of LLLT, EA and TENS treatment was stopped. CONCLUSION: TENS, EA and LLLT administered with optimal doses in an intensive 2-4 week treatment regimen, seem to offer clinically relevant short-term pain relief for OAK

    Search for direct pair production of the top squark in all-hadronic final states in proton-proton collisions at s√=8 TeV with the ATLAS detector

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    The results of a search for direct pair production of the scalar partner to the top quark using an integrated luminosity of 20.1fb−1 of proton–proton collision data at √s = 8 TeV recorded with the ATLAS detector at the LHC are reported. The top squark is assumed to decay via t˜→tχ˜01 or t˜→ bχ˜±1 →bW(∗)χ˜01 , where χ˜01 (χ˜±1 ) denotes the lightest neutralino (chargino) in supersymmetric models. The search targets a fully-hadronic final state in events with four or more jets and large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits are reported in terms of the top squark and neutralino masses and as a function of the branching fraction of t˜ → tχ˜01 . For a branching fraction of 100%, top squark masses in the range 270–645 GeV are excluded for χ˜01 masses below 30 GeV. For a branching fraction of 50% to either t˜ → tχ˜01 or t˜ → bχ˜±1 , and assuming the χ˜±1 mass to be twice the χ˜01 mass, top squark masses in the range 250–550 GeV are excluded for χ˜01 masses below 60 GeV

    Dual targeting of p53 and c-MYC selectively eliminates leukaemic stem cells

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    e Glasgow and Manchester Experimental Cancer Medicine Centres (ECMC), which are funded by CR-UK and the Chief Scientist’s Office (Scotland). We acknowledge the funders who have contributed to this work: MRC stratified medicine infrastructure award (A.D.W.), CR-UK C11074/A11008 (F.P., L.E.M.H., T.L.H., A.D.W.); LLR08071 (S.A.A., E.C.); LLR11017 (M.C.); SCD/04 (M.C.); LLR13035 (S.A.A., K.D., A.D.W., and A.P.); LLR14005 (M.T.S., D.V.); KKL690 (L.E.P.); KKL698 (P.B.); LLR08004 (A.D.W., A.P. and A.J.W.); MRC CiC (M.E.D.); The Howat Foundation (FACS support); Friends of Paul O’Gorman (K.D. and FACS support); ELF 67954 (S.A.A.); BSH start up fund (S.A.A.); MR/K014854/1 (K.D.)

    Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis using UK Biobank data: population based cohort study

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    Objective: To evaluate the benefit of combining polygenic risk scores with the QCancer-10 (colorectal cancer) prediction model for non-genetic risk to identify people at highest risk of colorectal cancer. Design: Population based cohort study. Setting: Data from the UK Biobank study, collected between March 2006 and July 2010. Participants: 434 587 individuals with complete data for genetics and QCancer-10 predictions were included in the QCancer-10 plus polygenic risk score modelling and validation cohorts. Main outcome measures: Prediction of colorectal cancer diagnosis by genetic, non-genetic, and combined risk models. Using data from UK Biobank, six different polygenic risk scores for colorectal cancer were developed using LDpred2 polygenic risk score software, clumping, and thresholding approaches, and a model based on genome-wide significant polymorphisms. The top performing genome-wide polygenic risk score and the score containing genome-wide significant polymorphisms were combined with QCancer-10 and performance was compared with QCancer-10 alone. Case-control (logistic regression) and time-to-event (Cox proportional hazards) analyses were used to evaluate risk model performance in men and women. Results: Polygenic risk scores derived using the LDpred2 program performed best, with an odds ratio per standard deviation of 1.584 (95% confidence interval 1.536 to 1.633), and top age and sex adjusted C statistic of 0.733 (95% confidence interval 0.710 to 0.753) in logistic regression models in the validation cohort. Integrated QCancer-10 plus polygenic risk score models out-performed QCancer-10 alone. In men, the integrated LDpred2 model produced a C statistic of 0.730 (0.720 to 0.741) and explained variation of 28.2% (26.3 to 30.1), compared with 0.693 (0.682 to 0.704) and 21.0% (18.9 to 23.1) for QCancer-10 alone. In women, the C statistic for the integrated LDpred2 model was 0.687 (0.673 to 0.702) and explained variation was 21.0% (18.7 to 23.7), compared with 0.645 (0.631 to 0.659) and 12.4% (10.3 to 14.6) for QCancer-10 alone. In the top 20% of individuals at highest absolute risk, the sensitivity and specificity of the integrated LDpred2 models for predicting colorectal cancer diagnosis was 47.8% and 80.3% respectively in men, and 42.7% and 80.1% respectively in women, with increases in absolute risk in the top 5% of risk in men of 3.47-fold and in women of 2.77-fold compared with the median. Illustrative decision curve analysis indicated a small incremental improvement in net benefit with QCancer-10 plus polygenic risk score models compared with QCancer-10 alone. Conclusions: Integrating polygenic risk scores with QCancer-10 modestly improves risk prediction over use of QCancer-10 alone. Given that QCancer-10 data can be obtained relatively easily from health records, use of polygenic risk score in risk stratified population screening for colorectal cancer currently has no clear justification. The added benefit, cost effectiveness, and acceptability of polygenic risk scores should be carefully evaluated in a real life screening setting before implementation in the general population

    Neuropsychiatric Events Associated with Leukotriene-Modifying Agents: A Systematic Review

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    Introduction: Leukotriene-modifying agents (LTMAs) including montelukast, zafirlukast, and zileuton are approved by the US Food and Drug Administration (FDA) for the treatment of asthma and allergic rhinitis. Various neuropsychiatric events (NEs) have been reported; however, the evidence of the association is conflicting. This systematic review investigates the association between NEs and LTMAs by assessing the relevant published literature. / Methods: PubMed, EMBASE, MEDLINE, and Cochrane Library were searched using keywords. Studies designed to investigate the association were eligible for inclusion without restriction to any study design or language. The primary outcome was defined as suicidal conditions, while secondary outcomes included all other NEs. / Results: Thirty-three studies were included for a narrative review. Four observational studies did not find a significant association, while ten pharmacovigilance studies using different global databases detected the signals. Notably, some studies suggest that the FDA warning issued in 2008 might have influenced the reporting rate of NEs as a result of increased awareness. / Limitations: The risk of NEs was not quantified, because of the lack of randomized controlled trials and observational studies investigating the association. / Conclusion: Many pharmacovigilance studies have been conducted to determine the association between NEs and LTMAs, but there is limited evidence from observational studies. High-quality epidemiological studies should be conducted to evaluate the association and quantify the risk, not only in children, but also in adults

    Overall Survival Time Prediction for High-grade Glioma Patients based on Large-scale Brain Functional Networks

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    High-grade glioma (HGG) is a lethal cancer with poor outcome. Accurate preoperative overall survival (OS) time prediction for HGG patients is crucial for treatment planning. Traditional presurgical and noninvasive OS prediction studies have used radiomics features at the local lesion area based on the magnetic resonance images (MRI). However, the highly complex lesion MRI appearance may have large individual variability, which could impede accurate individualized OS prediction. In this paper, we propose a novel concept, namely brain connectomics-based OS prediction. It is based on presurgical resting-state functional MRI (rs-fMRI) and the non-local, large-scale brain functional networks where the global and systemic prognostic features rather than the local lesion appearance are used to predict OS. We propose that the connectomics features could capture tumor-induced network-level alterations that are associated with prognosis. We construct both low-order (by means of sparse representation with regional rs-fMRI signals) and high-order functional connectivity (FC) networks (characterizing more complex multi-regional relationship by synchronized dynamics FC time courses). Then, we conduct a graph-theoretic analysis on both networks for a jointly, machine-learning-based individualized OS prediction. Based on a preliminary dataset (N = 34 with bad OS, mean OS, ~400 days; N = 34 with good OS, mean OS, ~1030 days), we achieve a promising OS prediction accuracy (86.8%) on separating the individuals with bad OS from those with good OS. However, if using only conventionally derived descriptive features (e.g., age and tumor characteristics), the accuracy is low (63.2%). Our study highlights the importance of the rs-fMRI and brain functional connectomics for treatment planning

    Fibulin-2 Is a Driver of Malignant Progression in Lung Adenocarcinoma

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    The extracellular matrix of epithelial tumors undergoes structural remodeling during periods of uncontrolled growth, creating regional heterogeneity and torsional stress. How matrix integrity is maintained in the face of dynamic biophysical forces is largely undefined. Here we investigated the role of fibulin-2, a matrix glycoprotein that functions biomechanically as an inter-molecular clasp and thereby facilitates supra-molecular assembly. Fibulin-2 was abundant in the extracellular matrix of human lung adenocarcinomas and was highly expressed in tumor cell lines derived from mice that develop metastatic lung adenocarcinoma from co-expression of mutant K-ras and p53. Loss-offunction experiments in tumor cells revealed that fibulin-2 was required for tumor cells to grow and metastasize in syngeneic mice, a surprising finding given that other intra-tumoral cell types are known to secrete fibulin-2. However, tumor cells grew and metastasized equally well in Fbln2-null and -wildtype littermates, implying that malignant progression was dependent specifically upon tumor cellderived fibulin-2, which could not be offset by other cellular sources of fibulin-2. Fibulin-2 deficiency impaired the ability of tumor cells to migrate and invade in Boyden chambers, to create a stiff extracellular matrix in mice, to cross-link secreted collagen, and to adhere to collagen. We conclude that fibulin-2 is a driver of malignant progression in lung adenocarcinoma and plays an unexpected role in collagen cross-linking and tumor cell adherence to collagen

    Search for supersymmetry in events with four or more leptons in √s =13 TeV pp collisions with ATLAS

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    Results from a search for supersymmetry in events with four or more charged leptons (electrons, muons and taus) are presented. The analysis uses a data sample corresponding to 36.1 fb −1 of proton-proton collisions delivered by the Large Hadron Collider at s √ =13 TeV and recorded by the ATLAS detector. Four-lepton signal regions with up to two hadronically decaying taus are designed to target a range of supersymmetric scenarios that can be either enriched in or depleted of events involving the production and decay of a Z boson. Data yields are consistent with Standard Model expectations and results are used to set upper limits on the event yields from processes beyond the Standard Model. Exclusion limits are set at the 95% confidence level in simplified models of General Gauge Mediated supersymmetry, where higgsino masses are excluded up to 295 GeV. In R -parity-violating simplified models with decays of the lightest supersymmetric particle to charged leptons, lower limits of 1.46 TeV, 1.06 TeV, and 2.25 TeV are placed on wino, slepton and gluino masses, respectively
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