Neurological complication of systemic cancer

Neurological complications of systemic cancer—those arising outside the nervous system—can be distressing, disabling, and sometimes fatal. Diagnosis is often difficult because different neurological disorders may present with similar signs and symptoms. Furthermore, comorbid neurological illnesses, common in elderly patients with cancer, can complicate diagnosis. Early diagnosis and aggressive treatment can improve neurological symptoms and can substantially enhance a patient's quality of life. We approach the problem of neurological complications of systemic cancer as would a neurologist: first by identifying the anatomical area or areas that are affected (ie, brain, spinal cord, peripheral nerve), then by evaluating the diagnostic approach, considering the symptoms and signs and including appropriate laboratory tests, and finally, by recommending treatment. We focus on disorders that are difficult to diagnose, need neurological consultation, and for which effective treatments exist.

Anti-angiogenic therapy for lung cancer

This is the protocol for a review and there is no abstract. The objectives are as follows:

To determine the benefits and harms of angiogenesis inhibitors in the treatment of lung cancer when given alone, following or in combination with chemotherapy or chemo-radiotherapy (in the case of locally advanced non-metastatic NSCLC or limited stage SCLC).

A multi-objective sensitivity approach to training providers' evaluation and quota allocation planning

The practice of solely relying on the human resources department in the selection process of external training providers has cast doubts and mistrust across other departments as to how trainers are sourced. There are no measurable criteria used by human resource personnel, since most decisions are based on intuitive experience and subjective market knowledge. The present problem focuses on outsourcing of private training programs that are partly government funded, which has been facing accountability challenges. Due to the unavailability of a scientific decision-making approach in this context, a 12-step algorithm is proposed and tested in a Japanese multinational company. The model allows the decision makers to revise their criteria expectations, in turn witnessing the change of the training providers' quota distribution. Finally, this multi-objective sensitivity analysis provides a forward-looking approach to training needs planning and aids decision makers in their sourcing strategy.

Primary systemic therapy in HER2-amplified breast cancer : a clinical review

Primary systemic therapy (PST) in early breast cancer is utilized in locally advanced breast tumors and when breast-conserving surgery is desirable. In addition, the PST setting provides an opportunity to monitor response including histopathological and biomarker examination of the tumor and host tissues before and after systemic therapy. Trastuzumab is a monoclonal antibody targeting the hEGF receptor that is overexpressed in 15–20% of breast tumors. Trastuzumab is effective in prolonging survival when used to treat women with hEGF receptor overexpressed tumors, both in adjuvant and metastatic disease settings. Trastuzumab has also shown promising activity in PST/neoadjuvant studies by achieving high rates of complete pathologic response. This is a review of clinical studies that incorporated trastuzumab in PST and/or neoadjuvant chemotherapy, including the results of recently reported studies using trastuzumab in combination with other novel therapies such as lapatinib or pertuzumab.

Student attention, engagement and participation in a Twitter-friendly classroom

Guided by a participatory action research methodology, this paper outlines an approach to integrating the social media Twitter platform within a tertiary education course, based on a social, constructivist pedagogy. It explores the perceptions of students on the benefits of using this technology for enhancing attentiveness, engagement and participation in the classroom. Previous studies have shown that greater participation and communication can stimulate student learning and lead to better academic performance, increased motivation, and an appreciation of different points of views. The untested hypothesis is that social media tools like Twitter can foster this type of communication. Students posted their responses during classroom activities via Twitter and then were surveyed on their perceived benefits associated with using the social media platform. The preliminary findings of the qualitative study suggest that, while not without its challenges, social media tools like Twitter have the potential to be used effectively for education-based activities in the classroom to improve communication and engagement both amongst the students and with the instructor.

The moderating influence of device characteristics and usage on user acceptance of Smart Mobile Devices

This study seeks to develop a comprehensive model of consumer acceptance in the context of Smart Mobile Device (SMDs). This paper proposes an adaptation of the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) model that can be employed to explain and predict the acceptance of SMDs. Also included in the model are a number of external and new moderating variables that can be used to explain user intentions and subsequent usage behaviour. The model holds that Activity-based Usage and Device Characteristics are posited to moderate the impact of the constructs empirically validated in the UTAUT2 model. Through an important cluster of antecedents the proposed model aims to enhance our understanding of consumer motivations for using SMDs and aid efforts to promote the adoption and diffusion of these devices.

Realist synthesis : illustrating the method for implementation research

Background
Realist synthesis is an increasingly popular approach to the review and synthesis of evidence, which focuses on understanding the mechanisms by which an intervention works (or not). There are few published examples of realist synthesis. This paper therefore fills a gap by describing, in detail, the process used for a realist review and synthesis to answer the question 'what interventions and strategies are effective in enabling evidence-informed healthcare?' The strengths and challenges of conducting realist review are also considered.
Methods
The realist approach involves identifying underlying causal mechanisms and exploring how they work under what conditions. The stages of this review included: defining the scope of the review (concept mining and framework formulation); searching for and scrutinising the evidence; extracting and synthesising the evidence; and developing the narrative, including hypotheses.
Results
Based on key terms and concepts related to various interventions to promote evidenceinformed healthcare, we developed an outcome-focused theoretical framework. Questions were tailored for each of four theory/intervention areas within the theoretical framework and were used to guide development of a review and data extraction process. The search for literature within our first theory area, change agency, was executed and the screening procedure resulted in inclusion of 52 papers. Using the questions relevant to this theory area, data were extracted by one reviewer and validated by a second reviewer. Synthesis involved organisation of extracted data into evidence tables, theming and formulation of chains of inference, linking between the chains of inference, and hypothesis formulation. The narrative was developed around the hypotheses generated within the change agency theory area.
Conclusions
Realist synthesis lends itself to the review of complex interventions because it accounts for context as well as outcomes in the process of systematically and transparently synthesising relevant literature. While realist synthesis demands flexible thinking and the ability to deal with complexity, the rewards include the potential for more pragmatic conclusions than alternative approaches to systematic reviewing. A separate publication will report the findings of the review.

Internet and distributed computing advancements : theoretical frameworks and practical applications

This book is a vital compendium of chapters on the latest research within the field of distributed computing, capturing trends in the design and development of Internet and distributed computing systems that leverage autonomic principles and techniques. The chapters provided within this collection offer a holistic approach for the development of systems that can adapt themselves to meet requirements of performance, fault tolerance, reliability, security, and Quality of Service (QoS) without manual intervention.

Network and traffic engineering in emerging distributed computing applications

This book focuses on network management and traffic engineering for Internet and distributed computing technologies, as well as present emerging technology trends and advanced platform

Management of service level agreement for service-oriented content adaptation platform

It is paramount to provide seamless and ubiquitous access to rich contents available online to interested users via a wide range of devices with varied characteristics. Recently, a service-oriented content adaptation scheme has emerged to address this content-device mismatch problem. In this scheme, content adaptation functions are provided as services by third-party providers. Clients pay for the consumed services and thus demand service quality. As such, negotiating for the QoS offers, assuring negotiated QoS levels and accuracy of adapted content version are essential. Any non-compliance should be handled and reported in real time. These issues elevate the management of service level agreement (SLA) as an important problem. This chapter presents prior work, important challenges, and a framework for managing SLA for service-oriented content adaptation platform.

Strategies for agent-based negotiation in e-trade

£-negotiation handles negotiation over the Internet without human supervision and has shown effectiveness in concluding verifiable and more favorable agreements in a reasonably short time. In this chapter, the authors discuss the negotiation 5ystem and its components with particular emphasis on negotiation strategies. A negotiation strategy defines strategic tactics, which advise on the proper action to select from a set of possible actions that optimizes negotiation outcomes. A strategy should integrate negotiation goals and reactive attitudes. Usually, a fixed strategy is implemented during the course of negotiation regardless ofsignificant decision-makingfactors including market status, opponent :S profile, or eagerness for a negotiated goods/service. The chapter presents the main negotiation strategies and outlines the different decision-makingfactors that should be considered. A strategy uses a utility function to evaluate the offer of an opponent and advises on the generation of a counter offer or the best interaction. The authors finally discuss different utility functions presented in the literature.

Using lithium as a neuroprotective agent in patients with cancer

Neurocognitive impairment is being increasingly recognized as an important issue in patients with cancer who develop cognitive difficulties either as part of direct or indirect involvement of the nervous system or as a consequence of either chemotherapy-related or radiotherapy-related complications. Brain radiotherapy in particular can lead to significant cognitive defects. Neurocognitive decline adversely affects quality of life, meaningful employment, and even simple daily activities. Neuroprotection may be a viable and realistic goal in preventing neurocognitive sequelae in these patients, especially in the setting of cranial irradiation. Lithium is an agent that has been in use for psychiatric disorders for decades, but recently there has been emerging evidence that it can have a neuroprotective effect.

This review discusses neurocognitive impairment in patients with cancer and the potential for investigating the use of lithium as a neuroprotectant in such patients.

Phase II trial of continuous low-dose temozolomide for patients with recurrent malignant glioma

Background In this phase II trial, we investigated the efficacy of a metronomic temozolomide schedule in the treatment of recurrent malignant gliomas (MGs).

Methods Eligible patients received daily temozolomide (50 mg/m2) continuously until progression. The primary endpoint was progression-free survival rate at 6 months in the glioblastoma cohort (N = 37). In an exploratory analysis, 10 additional recurrent grade III MG patients were enrolled. Correlative studies included evaluation of 76 frequent mutations in glioblastoma (iPLEX assay, Sequenom) aiming at establishing the frequency of potentially “drugable” mutations in patients entering recurrent MG clinical trials.

Results Among glioblastoma patients, median age was 56 y; median Karnofsky Performance Score (KPS) was 80; 62% of patients had been treated for ≥2 recurrences, including 49% of patients having failed bevacizumab. Treatment was well tolerated; clinical benefit (complete response + partial response + stable disease) was seen in 10 (36%) patients. Progression-free survival rate at 6 months was 19% and median overall survival was 7 months. Patients with previous bevacizumab exposure survived significantly less than bevacizumab-naive patients (median overall survival: 4.3 mo vs 13 mo; hazard ratio = 3.2; P = .001), but those patients had lower KPS (P = .04) and higher number of recurrences (P < .0001). Mutations were found in 13 of the 38 MGs tested, including mutations of EGFR (N = 10), IDH1 (N = 5), and ERBB2 (N = 1).

Conclusions In spite of a heavily pretreated population, including nearly half of patients having failed bevacizumab, the primary endpoint was met, suggesting that this regimen deserves further investigation. Results in bevacizumab-naive patients seemed particularly favorable, while results in bevacizumab-failing patients highlight the need to develop further treatment strategies for advanced MG.

EFP-M2 : efficient model for mining frequent patterns in transactional database

Discovering frequent patterns plays an essential role in many data mining applications. The aim of frequent patterns is to obtain the information about the most common patterns that appeared together. However, designing an efficient model to mine these patterns is still demanding due to the capacity of current database size. Therefore, we propose an Efficient Frequent Pattern Mining Model (EFP-M2) to mine the frequent patterns in timely manner. The result shows that the algorithm in EFP-M2l is outperformed at least at 2 orders of magnitudes against the benchmarked FP-Growth.