Search

Background and objectives: In patients with kidney failure due to IgA nephropathy, IgA deposits can recur in a subsequent kidney transplant. The incidence, effect, and risk factors of IgA nephropathy recurrence is unclear, because most studies have been single center and sample sizes are relatively small.Design, setting, participants, & measurements: We performed a multicenter, international, retrospective study to determine the incidence, risk factors, and treatment response of recurrent IgA nephropathy after kidney transplantation. Data were collected from all consecutive patients with biopsy-proven IgA nephropathy transplanted between 2005 and 2015, across 16 “The Post-Transplant Glomerular Disease” study centers in Europe, North America, and South America.Results: Out of 504 transplant recipients with IgA nephropathy, recurrent IgA deposits were identified by kidney biopsy in 82 patients; cumulative incidence of recurrence was 23% at 15 years (95% confidence interval, 14 to 34). Multivariable Cox regression revealed a higher risk for recurrence of IgA deposits in patients with a pre-emptive kidney transplant (hazard ratio, 3.45; 95% confidence interval, 1.31 to 9.17) and in patients with preformed donorspecific antibodies (hazardratio, 2.59; 95%confidence interval, 1.09 to 6.19).Afterkidneytransplantation,development of de novo donor-specific antibodies was associated with subsequent higher risk of recurrence of IgA nephropathy (hazard ratio, 6.65; 95% confidence interval, 3.33 to 13.27). Immunosuppressive regimen was not associated with recurrent IgA nephropathy in multivariable analysis, including steroid use. Graft loss was higher in patients with recurrence of IgA nephropathy compared with patients without (hazard ratio, 3.69; 95% confidence interval, 2.04 to 6.66), resulting in 32% (95% confidence interval, 50 to 82) graft loss at 8 years after diagnosis of recurrence.Conclusions: In our international cohort, cumulative risk of IgA nephropathy recurrence increased after transplant and was associated with a 3.7-fold greater risk of graft loss.

Cognitive radio networks (CRNs) are prone to emerging coexistence security threats such as primary user emulation attack (PUEA). Specifically, a malicious CRN may mimic licensees' [primary users (PUs)] signal characteristics to force another CRN to vacate its channels thinking that PUs have returned. While existing schemes are promising to some extent on detecting PUEAs, they are not able to prevent the attacks. In this article, the authors propose a PUEA deterrent (PUED) algorithm that can provide PUEAs' commission details: offender CRNs and attacks' time and bandwidth. There are many similarities between PUED and closed‐circuit television (CCTV) in terms of: deterrence strategy, reason for use, surveillance characteristics, surveillance outcome, and operation site. According to the criminology literature, robust CCTV systems have shown a significant reduction in visible offences (e.g. vehicle theft), reducing crime rates by 80%. Similarly, PUED will contribute the same effectiveness in deterring PUEAs. Furthermore, providing PUEAs' details will prevent the network's cognitive engine from considering the attacks as real PUs, consequently avoiding devising unreliable spectrum models for the attacked channels. Extensive simulations show the effectiveness of the PUED algorithm in terms of improving CRNs' performance.

Background and objectives FSGS recurrence after kidney transplantation is a major risk factor for graft loss. However, the natural history, clinical predictors, and response to treatment remain unclear because of small sample sizes and poor generalizability of single-center studies, and disease misclassification in registry-based studies. We therefore aimed to determine the incidence, predictors, and treatment response of recurrent FSGS in a large cohort of kidney transplant recipients. Design, setting, participants, & measurements The Post-Transplant Glomerular Disease (TANGO) project is an observational, multicenter, international cohort study that aims to investigate glomerular disease recurrence post-transplantation. Transplant recipients were screened for the diagnosis of idiopathic FSGS between 2005 and 2015 and details were recorded about the transplant, clinical outcomes, treatments, and other risk factors. Results Among 11,742 kidney transplant recipients screened for FSGS, 176 had a diagnosis of idiopathic FSGS and were included. FSGS recurred in 57 patients (32%; 95% confidence interval [95% CI], 25% to 39%) and 39% of them lost their graft over a median of 5 (interquartile range, 3.0–8.1) years. Multivariable Cox regression revealed a higher risk for recurrence with older age at native kidney disease onset (hazard ratio [HR], 1.37 per decade; 95% CI, 1.09 to 1.56). Other predictors were white race (HR, 2.14; 95% CI, 1.08 to 4.22), body mass index at transplant (HR, 0.89 per kg/m2; 95% CI, 0.83 to 0.95), and native kidney nephrectomies (HR, 2.76; 95% CI, 1.16 to 6.57). Plasmapheresis and rituximab were the most frequent treatments (81%). Partial or complete remission occurred in 57% of patients and was associated with better graft survival. Conclusions Idiopathic FSGS recurs post-transplant in one third of cases and is associated with a five-fold higher risk of graft loss. Response to treatment is associated with significantly better outcomes but is achieved in only half of the cases.

Background. Patients undergoing kidney transplantation have increased risk of adverse cardiovascular events due to histories of hypertension, end-stage renal disease, and dialysis. As such, they are especially in need of accurate preoperative risk assessment. Methods. We compared three different risk assessment models for their ability to predict major adverse cardiac events at 30 days and 1 year after transplant. These were the PORT model, the RCRI model, and the Gupta model. We used a method based on generalized U-statistics to determine statistically significant improvements in the area under the receiver operator curve (AUC), based on a common major adverse cardiac event (MACE) definition. For the top-performing model, we added new covariates into multivariable logistic regression in an attempt to create further improvement in the AUC. Results. The AUCs for MACE at 30 days and 1 year were 0.645 and 0.650 (PORT), 0.633 and 0.661 (RCRI), and finally 0.489 and 0.557 (Gupta), respectively. The PORT model performed significantly better than the Gupta model at 1 year (p=0.039). When the sensitivity was set to 95%, PORT had a significantly higher specificity of 0.227 compared to RCRI’s 0.071 (p=0.009) and Gupta’s 0.08 (p=0.017). Our additional covariates increased the receiver operator curve from 0.664 to 0.703, but this did not reach statistical significance (p=0.278). Conclusions. Of the three calculators, PORT performed best when the sensitivity was set at a clinically relevant level. This is likely due to the unique variables the PORT model uses, which are specific to transplant patients.

Inter Cell Interference (ICI) is a major challenge that degrades the performance of mobile systems, particularly\ud for cell-edge users. This problem arises significantly in the next generation system, as the trend of deployment is with high densification, which yields an ultra-dense network (UDN). One of the challenges in UDN is the dramatic increase of ICI from surrounding cells. A common technique to minimise ICI is interference coordination techniques. In this context, the most efficient ICI coordination is fractional frequency reuse (FFR).\ud This paper investigates the FFR in UDN millimetre wave\ud network at 26GHz band. The focus is on dense network with short inter site distance (ISD), and higher order sectorisation (HOS). The metrics used in frequency reuse is the signal to interference plus noise ratio (SINR) rather than the distance, as the line of sight in millimetre wave can be easily blocked by obstacles even if they are in close proximity to the serving base station. The work shows that FFR can improve the network performance in terms of per user cell-edge data throughput and average cell throughput, and maintain the peak data throughput\ud at a certain threshold. Furthermore, HOS has a potential gain over default sectored cells when the interference is carefully coordinated. The results show optimal values for bandwidth split per each scenario in FFR scheme to give the best trade-off between inner and outer zone users performance.

Two mechanisms have been proposed independently by IEEE and 3GPP; namely, Media Independent\ud Handover (MIH) and Access Network Discovery and Selection Function (ANDSF), respectively. These\ud mechanisms enable a seamless Vertical Handover (VHO) between the different types of technologies\ud (3GPP and non-3GPP), such as GSM (Global System for Mobile Communication), Wireless Fidelity (Wi-\ud Fi), Worldwide Interoperability for Microwave Access (WiMAX), Universal Mobile Telecommunications\ud System (UMTS) and Long Term Evolution (LTE). In this paper, we overview these mechanisms and show\ud their components, benefits and drawbacks. Then we present our Imperative Alternative MIH for Vertical\ud Handover (I AM 4 VHO) approach based on the approaches that have been studied in the literature with\ud better performance (packet loss and latency), less connection failure (probability of reject sessions), less\ud complexity and more exhaustive for enhancing VHO heterogeneous wireless networks environment.

In this paper, a predistortion neural network (PDNN) architecture has been imposed to the Sniffer Mobile Robot (SNFRbot) that is based on spatial multiplexed wireless Orthogonal Frequency Division Multiplexing (OFDM) transmission technology. This proposal is used to improve the system performance by combating one of the main drawbacks that is encountered by OFDM technology; Peak-to-Average Power Ratio (PAPR). Simulation results show that using PDNN resulted in better PAPR performance than the previously published work that is based on linear coding, such as Low Density Parity Check (LDPC) codes and turbo encoding whether using flat fading channel or a Doppler spread channel.

The September 2001 attacks and the 2011 Japan earthquake and tsunami disaster are examples of manmade and natural disasters which have revealed the importance of having a disaster management system in place. A great deal of advisory and policy documents need to be developed by various government authorities. The Intelligent Transportation Systems and Services (ITSS) are set to play a crucial role in responding to emergencies and large-scale disasters.\ud \ud In previous works, we have proposed and evaluated an intelligent disaster management system based on the emerging ICT technologies such as Vehicular Ad hoc Networks (VANETs) and Cloud Computing with a focus on transportation in urban environments. Also, we have developed a tool to examine previous proposed intelligent system performance in improving the transportation evacuation strategies, and Demand Strategy (DS) has been shown as one of the various evacuation strategies to measure the improvements. In this paper, we applied and evaluated another transportation evacuation strategy called Speed Strategy (SS), independently for traffic network. In addition, the driver response to the emergency situations and their behaviors in travel choices may be difficult to quantify theoretically, however, driver response to evacuation pre-plans is part of the tool design and we present the importance of this factor through various evacuation strategies.