Pretransplant AT1R-Abs is an independent risk factor for AR, especially acute cellular rejection, and is possibly associated with the risk of antibody-mediated injury. Pretransplant assessment of AT1R-Abs may be useful for stratifying immunologic risks.
The results of this study show that the Dynesys system could preserve the motion of stabilized segments and provide clinical improvement in patients with degenerative spinal stenosis with instability. Thus, dynamic stabilization systems with adequate decompression may be an alternative surgical option to conventional fusion in selected patients.
Minimum variance (MV) beamforming has been studied for improving the performance of a diagnostic ultrasound imaging system. However, it is not easy for the MV beamforming to be implemented in a real-time ultrasound imaging system because of the enormous amount of computation time associated with the covariance matrix inversion. In this paper, to address this problem, we propose a new fast MV beamforming method that almost optimally approximates the MV beamforming while reducing the computational complexity greatly through dimensionality reduction using principal component analysis (PCA). The principal components are estimated offline from pre-calculated conventional MV weights. Thus, the proposed method does not directly calculate the MV weights but approximates them by a linear combination of a few selected dominant principal components. The combinational weights are calculated in almost the same way as in MV beamforming, but in the transformed domain of beamformer input signal by the PCA, where the dimension of the transformed covariance matrix is identical to the number of some selected principal component vectors. Both computer simulation and experiment were carried out to verify the effectiveness of the proposed method with echo signals from simulation as well as phantom and in vivo experiments. It is confirmed that our method can reduce the dimension of the covariance matrix down to as low as 2 × 2 while maintaining the good image quality of MV beamforming.
BackgroundAsian patients undergoing kidney transplantation (KT) generally have better renal allograft survival and a lower burden of cardiovascular disease than those of other racial groups. The KNOW-KT aims to explore allograft survival rate, cardiovascular events, and metabolic profiles and to elucidate the risk factors in Korean KT patients.MethodsKNOW-KT is a multicenter, observational cohort study encompassing 8 transplant centers in the Republic of Korea. KNOW-KT will enroll 1,000 KT recipients between 2012 and 2015 and follow them up to 9 years. At the time of KT and at pre-specified intervals, clinical information, laboratory test results, and functional and imaging studies on cardiovascular disease and metabolic complications will be recorded. Comorbid status will be assessed by the age-adjusted Charlson co-morbidity index. Medication adherence and information on quality of life (QoL) will be monitored periodically. The QoL will be assessed by the Kidney Disease Quality of Life Short Form. Donors will include both living donors and deceased donors whose status will be assessed by the Kidney Donor Risk Index. Primary endpoints include graft loss and patient mortality. Secondary endpoints include renal functional deterioration (a decrease in eGFR to <30 mL/min/1.73 m2), acute rejection, cardiovascular event, albuminuria, new-onset diabetes after transplant, and QoL. Data on other adverse outcomes including episodes of infection, malignancy, recurrence of original renal disease, fracture, and hospitalization will also be collected. A bio-bank has been established for the acquisition of DNA, RNA, and protein from serum and urine samples of recipients at regular intervals. Bio-samples from donors will also be collected at the time of KT. KNOW-KT was registered in an international clinical trial registry (NCT02042963 at http://www.clinicaltrials.gov) on January 20th, 2014.ConclusionThe KNOW-KT, the first large-scale cohort study in Asian KT patients, is expected to represent the Asian KT population and provide information on their natural course, complications, and risk factors for complications.
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