93 research outputs found

    Making Outbound Route Selection Robust to Egress Point Failure

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    Offline inter-domain outbound Traffic Engineering (TE) can be formulated as an optimization problem whose objective is to determine primary egress points for traffic exiting a domain. However, when egress point failures happen, congestion may occur if secondary egress points are not carefully determined. In this paper, we formulate a bi-level outbound TE problem in order to make outbound route selection robust to egress point failures. We propose a tabu search heuristic to solve the problem and compare the performance to three alternative approaches. Simulation results demonstrate that the tabu search heuristic achieves the best performance in terms of our optimization objectives and also keeps traffic disruption to a minimum

    An empirical study on the interactions between ALTO-assisted P2P overlays and ISP networks

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    The recently proposed Application Layer Traffic Optimization (ALTO) framework has opened up a new dimension for Internet traffic management that is complementary to the traditional application-agnostic traffic engineering (AATE) solutions currently employed by ISPs. In this paper, we investigate how ALTO-assisted Peer-to-Peer (P2P) traffic management functions interact with the underlying AATE operations, given that there may exist different application-layer policies in the P2P overlay. By considering specific P2P peer selection behaviors on top of a traffic-engineered ISP network, we conduct a performance analysis on how the application and network-layer respective performance is influenced by different policies at the P2P side. Our empirical study offers significant insight for the future design and analysis of cross-layer network engineering approaches that involve multiple autonomous optimization entities with both consistent and non-consistent policies

    An Integrated Network Management Framework for Inter-domain Outbound Traffic Engineering

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    This paper proposes an integrated network management framework for inter-domain outbound traffic engineering. The framework consists of three functional blocks (monitoring, optimization and implementation) to make the outbound traffic engineering adaptive to network condition changes such as inter-domain traffic demand variation, inter-domain routing changes and link failures. The objective is to keep the inter-domain link utilization balanced under any of these changes while reducing service disruptions and reconfiguration overheads. Simulation results demonstrate that the proposed framework can achieve better load balancing with less service disruptions and re-configuration overheads in comparison to alternative approaches

    Joint optimization of intra- and inter-autonomous system traffic engineering

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    Abstract: Traffic Engineering (TE) involves network configuration in order to achieve optimal IP network performance. The existing literature considers intra- and inter-AS (Autonomous System) TE independently. However, if these two aspects are considered separately, the overall network performance may not be truly optimized. This is due to the interaction between intra and inter-AS TE, where a good solution of inter-AS TE may not be good for intra-AS TE. To remedy this situation, we propose a joint optimization of intra- and inter-AS TE in order to improve the overall network performance by simultaneously finding the best egress points for inter-AS traffic and the best routing scheme for intra-AS traffic. Three strategies are presented to attack the problem, sequential, nested and integrated optimization. Our evaluation shows that, in comparison to sequential and nested optimization, integrated optimization can significantly improve overall network performance by being able to accommodate approximately 30%-60% more traffic demand

    Joint Optimization of Intra- and Inter-Autonomous System Traffic Engineering

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    Traffic Engineering (TE) is used to optimize IP operational network performance. The existing literature generally considers intra- and inter-AS (Autonomous System) TE independently. However, the overall network performance may not be truly optimized when these aspects are considered separately. This is due to the interaction between intra- and inter-AS TE, where a solution of intra-AS TE may not be a good input to inter-AS TE and vice versa. To remedy this situation, we propose considering intra-AS aspects during inter-AS TE and vice versa. We propose a joint optimization of intra- and inter-AS TE to further improve the overall network performance by simultaneously finding the best egress points for the inter-AS traffic and the best routing scheme for the intra-AS traffic. Three strategies are presented to attack the problem, namely sequential, nested and integrated optimization. Our simulation study shows that, compared to sequential and nested optimization, integrated optimization can significantly improve the overall network performance by accommodating 30%-60% more traffic demands

    Secretome-Based Identification of ULBP2 as a Novel Serum Marker for Pancreatic Cancer Detection

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    BACKGROUND: To discover novel markers for improving the efficacy of pancreatic cancer (PC) diagnosis, the secretome of two PC cell lines (BxPC-3 and MIA PaCa-2) was profiled. UL16 binding protein 2 (ULBP2), one of the proteins identified in the PC cell secretome, was selected for evaluation as a biomarker for PC detection because its mRNA level was also found to be significantly elevated in PC tissues. METHODS: ULBP2 expression in PC tissues from 67 patients was studied by immunohistochemistry. ULBP2 serum levels in 154 PC patients and 142 healthy controls were measured by bead-based immunoassay, and the efficacy of serum ULBP2 for PC detection was compared with the widely used serological PC marker carbohydrate antigen 19-9 (CA 19-9). RESULTS: Immunohistochemical analyses revealed an elevated expression of ULPB2 in PC tissues compared with adjacent non-cancerous tissues. Meanwhile, the serum levels of ULBP2 among all PC patients (n = 154) and in early-stage cancer patients were significantly higher than those in healthy controls (p<0.0001). The combination of ULBP2 and CA 19-9 outperformed each marker alone in distinguishing PC patients from healthy individuals. Importantly, an analysis of the area under receiver operating characteristic curves showed that ULBP2 was superior to CA 19-9 in discriminating patients with early-stage PC from healthy controls. CONCLUSIONS: Collectively, our results indicate that ULBP2 may represent a novel and useful serum biomarker for pancreatic cancer primary screening

    Bioinformatic identification of proteins with tissue-specific expression for biomarker discovery

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    <p>Abstract</p> <p>Background</p> <p>There is an important need for the identification of novel serological biomarkers for the early detection of cancer. Current biomarkers suffer from a lack of tissue specificity, rendering them vulnerable to non-disease-specific increases. The present study details a strategy to rapidly identify tissue-specific proteins using bioinformatics.</p> <p>Methods</p> <p>Previous studies have focused on either gene or protein expression databases for the identification of candidates. We developed a strategy that mines six publicly available gene and protein databases for tissue-specific proteins, selects proteins likely to enter the circulation, and integrates proteomic datasets enriched for the cancer secretome to prioritize candidates for further verification and validation studies.</p> <p>Results</p> <p>Using colon, lung, pancreatic and prostate cancer as case examples, we identified 48 candidate tissue-specific biomarkers, of which 14 have been previously studied as biomarkers of cancer or benign disease. Twenty-six candidate biomarkers for these four cancer types are proposed.</p> <p>Conclusions</p> <p>We present a novel strategy using bioinformatics to identify tissue-specific proteins that are potential cancer serum biomarkers. Investigation of the 26 candidates in disease states of the organs is warranted.</p

    Burden of Illness and Quality of Life in Tuberous Sclerosis Complex: Findings From the TOSCA Study

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    Research on tuberous sclerosis complex (TSC) to date has focused mainly on the physical manifestations of the disease. In contrast, the psychosocial impact of TSC has received far less attention. The aim of this study was therefore to examine the impact of TSC on health, quality of life (QoL), and psychosocial well-being of individuals with TSC and their families. Questionnaires with disease-specific questions on burden of illness (BOI) and validated QoL questionnaires were used. After completion of additional informed consent, we included 143 individuals who participated in the TOSCA (TuberOus SClerosis registry to increase disease Awareness) study. Our results highlighted the substantial burden of TSC on the personal lives of individuals with TSC and their families. Nearly half of the patients experienced negative progress in their education or career due to TSC (42.1%), as well as many of their caregivers (17.6% employed; 58.8% unemployed). Most caregivers (76.5%) indicated that TSC affected family life, and social and working relationships. Further, well-coordinated care was lacking: a smooth transition from pediatric to adult care was mentioned by only 36.8% of adult patients, and financial, social, and psychological support in 21.1, 0, and 7.9%, respectively. In addition, the moderate rates of pain/discomfort (35%) and anxiety/depression (43.4%) reported across all ages and levels of disease demonstrate the high BOI and low QoL in this vulnerable population

    The controversy of patellar resurfacing in total knee arthroplasty: Ibisne in medio tutissimus?

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    Early arthroplasty designs were associated with a high level of anterior knee pain as they failed to cater for the patello-femoral joint. Patellar resurfacing was heralded as the saviour safeguarding patient satisfaction and success but opinion on its necessity has since deeply divided the scientific community and has become synonymous to topics of religion or politics. Opponents of resurfacing contend that the native patella provides better patellar tracking, improved clinical function, and avoids implant-related complications, whilst proponents argue that patients have less pain, are overall more satisfied, and avert the need for secondary resurfacing. The question remains whether complications associated with patellar resurfacing including those arising from future component revision outweigh the somewhat increased incidence of anterior knee pain recorded in unresurfaced patients. The current scientific literature, which is often affected by methodological limitations and observer bias, remains confusing as it provides evidence in support of both sides of the argument, whilst blinded satisfaction studies comparing resurfaced and non-resurfaced knees generally reveal equivalent results. Even national arthroplasty register data show wide variations in the proportion of patellar resurfacing between countries that cannot be explained by cultural differences alone. Advocates who always resurface or never resurface indiscriminately expose the patella to a random choice. Selective resurfacing offers a compromise by providing a decision algorithm based on a propensity for improved clinical success, whilst avoiding potential complications associated with unnecessary resurfacing. Evidence regarding the validity of selection criteria, however, is missing, and the decision when to resurface is often based on intuitive reasoning. Our lack of understanding why, irrespective of pre-operative symptoms and patellar resurfacing, some patients may suffer pain following TKA and others may not have so far stifled our efforts to make the strategy of selective resurfacing succeed. We should hence devote our efforts in defining predictive criteria and indicators that will enable us to reliably identify those individuals who might benefit from a resurfacing procedure. Level of evidence V
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