77 research outputs found

    Survivorship and Clinical Outcome of the Minimally Invasive Uniglide Medial Fixed Bearing, All-polyethylene Tibia, Unicompartmental Knee Arthroplasty at a Mean Follow-up of 7.3 Years

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    Background: Medial UKA performed in England and Wales represents 7 to 11% of all knee arthroplasty procedures, and is most commonly performed using mobile-bearing designs. Fixed bearing eliminates the risk of bearing dislocation, however some studies have shown higher revision rates for all-polyethylene tibial components compared to those that utilize metal-backed implants. The aim of the study is to analyse survivorship and maximum 8-year clinical outcome of medial fixed bearing, Uniglide unicompartmental knee arthroplasty performed using an all-polyethylene tibial component with a minimal invasive approach. Methods: Between 2002 and 2009, 270 medial fixed UKAs were performed in our unit. Patients were reviewed pre-operatively, 5 and 8 years post-operatively. Clinical and radiographic reviews were carried out. Patients’ outcome scores (Oxford, WOMAC and American Knee Score) were documented in our database and analysed. Results: Survival and clinical outcome data of 236 knees with a mean 7.3 years follow-up are reported. Every patient with less than 4.93 years follow-up underwent a revision. The patients’ average age at the time of surgery was 69.5 years. The American Knee Society Pain and Function scores, the Oxford Knee Score and the WOMAC score all improved significantly. The 5 years survival rate was 94.1% with implant revision surgery as an end point. The estimated 10 years survival rate is 91.3%. 14 patients were revised before the 5 year follow-up. Conclusion: Fixed bearing Uniglide UKA with an all-polyethylene tibial component is a valuable tool in the management of a medial compartment osteoarthritis, affording good short term survivorship

    New insights into the genetic etiology of Alzheimer's disease and related dementias

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    Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

    MFTF TOTAL benchmark

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    A benchmark of the TOTAL data base management system as applied to the Mirror Fusion Test Facility (MFTF) data base was implemented and run in February and March of 1979. The benchmark was run on an Interdata 8/32 and involved the following tasks: (1) data base design, (2) data base generation, (3) data base load, and (4) develop and implement programs to simulate MFTF usage of the data base

    Two Sophisticated Techniques to Improve HMM-Based Intrusion Detection Systems

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    Abstract. Hidden Markov model (HMM) has been successfully applied to anomlay detection as a technique to model normal behavior. Despite its good performance, there are some problems in applying it to real intrusion detection systems: it requires large amount of time to model normal behaviors and the false-positive error rate is relatively high. To remedy these problems, we have proposed two techniques: extracting privilege flows to reduce the normal behaviors and combining multiple models to reduce the false-positive error rate. Experimental results with real audit data show that the proposed method requires significantly shorter time to train HMM without loss of detection rate and significantly reduces the false-positive error rate
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