Frequent activating FGFR2 mutations in endometrial carcinomas parallel germline mutations associated with craniosynostosis and skeletal dysplasia syndromes

Endometrial carcinoma is the most common gynecological malignancy in the United States. Although most women present with early disease confined to the uterus, the majority of persistent or recurrent tumors are refractory to current chemotherapies. We have identified a total of 11 different FGFR2 mutations in 3/10 (30%) of endometrial cell lines and 19/187 (10%) of primary uterine tumors. Mutations were seen primarily in tumors of the endometrioid histologic subtype (18/115 cases investigated, 16%). The majority of the somatic mutations identified were identical to germline activating mutations in FGFR2 and FGFR3 that cause Apert Syndrome, Beare-Stevenson Syndrome, hypochondroplasia, achondroplasia and SADDAN syndrome. The two most common somatic mutations identified were S252W (in eight tumors) and N550K (in five samples). Four novel mutations were identified, three of which are also likely to result in receptor gain-of-function. Extensive functional analyses have already been performed on many of these mutations, demonstrating they result in receptor activation through a variety of mechanisms. The discovery of activating FGFR2 mutations in endometrial carcinoma raises the possibility of employing anti-FGFR molecularly targeted therapies in patients with advanced or recurrent endometrial carcinoma.

Sulfate anion templation of macrocycles, capsules, interpenetrated and interlocked structures

This review examines the potential of anions, in particular sulfate, to template the formation of complex molecular architectures. Until recently, sulfate has been largely overlooked in this area and the examples described herein demonstrate this anion’s versatility in templating the formation of a diverse range of molecular systems including macrocycles, helixes, molecular capsules, interpenetrated and interlocked assemblies such as catenanes. In addition sulfate has been shown to template the formation of interpenetrated structures on a range of solid surfaces including gold, polystyrene beads and silicate nanoparticles, highlighting the potential of this anion in the fabrication of functional sensory devices exhibiting highly selective binding behaviour.

Ambient temperature and morbidity: A review of epidemiological evidence

OBJECTIVE: This paper reviews the epidemiological evidence on the relationship between ambient temperature and morbidity. It assesses the methodological issues in previous studies, and proposes future research directions. DATA SOURCES AND DATA EXTRACTION: We searched the PubMed database for epidemiological studies on ambient temperature and morbidity of non-communicable diseases published in refereed English journals prior to June 2010. 40 relevant studies were identified. Of these, 24 examined the relationship between ambient temperature and morbidity, 15 investigated the short-term effects of heatwave on morbidity, and 1 assessed both temperature and heatwave effects. DATA SYNTHESIS: Descriptive and time-series studies were the two main research designs used to investigate the temperature–morbidity relationship. Measurements of temperature exposure and health outcomes used in these studies differed widely. The majority of studies reported a significant relationship between ambient temperature and total or cause-specific morbidities. However, there were some inconsistencies in the direction and magnitude of non-linear lag effects. The lag effect of hot temperature on morbidity was shorter (several days) compared to that of cold temperature (up to a few weeks). The temperature–morbidity relationship may be confounded and/or modified by socio-demographic factors and air pollution. CONCLUSIONS: There is a significant short-term effect of ambient temperature on total and cause-specific morbidities. However, further research is needed to determine an appropriate temperature measure, consider a diverse range of morbidities, and to use consistent methodology to make different studies more comparable.

The measurement of information system use: preliminary considerations

The concept of system use has suffered from a "too simplistic definition" (DeLone and McLean [9], p. 16). This paper reviews various attempts at conceptualization and measurement of system use and then proposes a re-conceptualization of it as "the level of incorporation of an information system within a user's processes." We then go on to develop the concept of a Functional Interface Point and four dimensions of system usage: automation level, the proportion of the business process encoded by the information system; extent, the proportion of the FIPs used by the business process; frequency, the rate at which FIPs are used by the participants in the process; and thoroughness, the level of use of information/functionality provided by the system at an FIP. The article concludes with a discussion of some implications of this re-conceptualization and areas for follow on research.

High-Order Concept Associations Mining and Inferential Language Modeling for Online Review Spam Detection

Despite many incidents about fake online consumer reviews have been reported, very few studies have been conducted to date to examine the trustworthiness of online consumer reviews. One of the reasons is the lack of an effective computational method to separate the untruthful reviews (i.e., spam) from the legitimate ones (i.e., ham) given the fact that prominent spam features are often missing in online reviews. The main contribution of our research work is the development of a novel review spam detection method which is underpinned by an unsupervised inferential language modeling framework. Another contribution of this work is the development of a high-order concept association mining method which provides the essential term association knowledge to bootstrap the performance for untruthful review detection. Our experimental results confirm that the proposed inferential language model equipped with high-order concept association knowledge is effective in untruthful review detection when compared with other baseline methods.

Data preprocessing for anomaly based network intrusion detection : a review

Data preprocessing is widely recognized as an important stage in anomaly detection. This paper reviews the data preprocessing techniques used by anomaly-based network intrusion detection systems (NIDS), concentrating on which aspects of the network traffic are analyzed, and what feature construction and selection methods have been used. Motivation for the paper comes from the large impact data preprocessing has on the accuracy and capability of anomaly-based NIDS. The review finds that many NIDS limit their view of network traffic to the TCP/IP packet headers. Time-based statistics can be derived from these headers to detect network scans, network worm behavior, and denial of service attacks. A number of other NIDS perform deeper inspection of request packets to detect attacks against network services and network applications. More recent approaches analyze full service responses to detect attacks targeting clients. The review covers a wide range of NIDS, highlighting which classes of attack are detectable by each of these approaches. Data preprocessing is found to predominantly rely on expert domain knowledge for identifying the most relevant parts of network traffic and for constructing the initial candidate set of traffic features. On the other hand, automated methods have been widely used for feature extraction to reduce data dimensionality, and feature selection to find the most relevant subset of features from this candidate set. The review shows a trend toward deeper packet inspection to construct more relevant features through targeted content parsing. These context sensitive features are required to detect current attacks.

Evaluating educational software : a historical overview and the challenges ahead

Teachers are under increasing pressure from government and school management to incorporate technology into lessons. They need to consider which technologies can most effectively enhance subject learning, encourage higher order thinking skills and support the performance of authentic tasks. This chapter reviews the practical and theoretical tools that have been developed to aid teachers in selecting software and reviews the software assessment methodologies from the 1980s to the present day. It concludes that teachers need guidance to structure the evaluation of technology, to consider its educational affordances, its usability, its suitability for the students and the classroom environment and its fit to the teachers’ preferred pedagogies.

Prevalence of malnutrition in Parkinson's disease : a systematic review

Parkinson's disease (PD) patients may be at higher risk of malnutrition because of the symptoms associated with the disease and the side effects of the medication used to manage it. A decline in nutritional status is associated with many adverse outcomes related to health and quality of life. It is not clear, however, to what extent this population is currently affected by malnutrition. The objective of this review was to systematically assess the methodology and outcomes of studies reporting the prevalence of malnutrition in PD patients. Studies that attempted to classify participants with PD into nutritional risk and/or malnutrition categories using body mass index, weight change, anthropometric measures, and nutritional screening and assessment scores were included. The prevalence of malnutrition ranged from 0% to 24% in PD patients, while 3–60% of PD patients were reported to be at risk of malnutrition. There was a large degree of variation among studies in the methods chosen, the definition of malnutrition using those methods, and the detail in which the methodological protocols were reported. The true extent of malnutrition in the PD population has yet to be accurately quantified. It is important, however, to screen for malnutrition at the time of PD diagnosis.

Leveraging Web 2.0 data for scalable semi-supervised learning of domain-specific sentiment lexicons

Since manually constructing domain-specific sentiment lexicons is extremely time consuming and it may not even be feasible for domains where linguistic expertise is not available. Research on the automatic construction of domain-specific sentiment lexicons has become a hot topic in recent years. The main contribution of this paper is the illustration of a novel semi-supervised learning method which exploits both term-to-term and document-to-term relations hidden in a corpus for the construction of domain specific sentiment lexicons. More specifically, the proposed two-pass pseudo labeling method combines shallow linguistic parsing and corpusbase statistical learning to make domain-specific sentiment extraction scalable with respect to the sheer volume of opinionated documents archived on the Internet these days. Another novelty of the proposed method is that it can utilize the readily available user-contributed labels of opinionated documents (e.g., the user ratings of product reviews) to bootstrap the performance of sentiment lexicon construction. Our experiments show that the proposed method can generate high quality domain-specific sentiment lexicons as directly assessed by human experts. Moreover, the system generated domain-specific sentiment lexicons can improve polarity prediction tasks at the document level by 2:18% when compared to other well-known baseline methods. Our research opens the door to the development of practical and scalable methods for domain-specific sentiment analysis.

Sequestration through forestry and agriculture

Current climate mitigation policies have not fully resolved contentious issues regarding the inclusion of carbon sequestration through changes in forestry and agricultural management practices. Terrestrial carbon sinks could be a low-cost mitigation option that fosters conservation and development, yet issues related to accurately documenting the amount of carbon sequestered undermine confidence that emission offsets through sequestration are equivalent to emission reductions. From an atmospheric perspective, net of CO2 removals through sequestration are equivalent to emission reductions over a given period of time. But carbon will not remain sequestered in biomass or soils indefinitely and investments in sequestration could stifle investments in reducing emissions from other sources. Many international climate agreements cap emissions from some countries or sectors but enable participation of uncapped countries or sectors for forestry and agricultural sequestration. This structure can prompt emission increases in parts of the uncapped entities that weaken the value of emission reductions earned through sequestration. This has been a minor issue under the Clean Development Mechanism of the Kyoto Protocol. Reduced emissions through deforestation and degradation is susceptible to the same problems. The purpose of this article is to review the science, politics, and policy that form the basis of arguments for and against the inclusion forestry and agricultural sequestration as a component of current and future international climate mitigation policies.

Implementing design build project delivery system in Indonesian road infrastructure projects

Design-Build (DB) project delivery systems have increasingly been adopted by many private and public sector organizations worldwide due to its many advantages. However, many Indonesian road infrastructure projects are still delivered using the traditional design-bid-build (DBB) project delivery system. This paper reviews the existing literature to explore factors that can influence the successful implementation of DB project delivery system in Indonesian road infrastructure projects. It founds the lack of clarification in existing legislations as well as the lack of experiences, knowledge and skill as the main obstacles in implementing DB systems in Indonesia. To overcome these obstacles, this paper proposes (1) A relook at existing legislation in term of providing more guidance on determining projects appropriate for the DB, procedures for implementing DB, and the structure of builder entity; (2) To develop the skills and knowledge of DB to all stakeholders through communications, knowledge sharing and training. The outcome of this review can serve as a guide to development a framework for the implementation of the design-build project delivery system in Indonesian road infrastructure projects.

Quality of life of women with lower-limb lymphedema following gynecological cancer

Secondary lower-limb lymphedema can develop following treatment for gynecological cancers, and has debilitating effects on quality of life (QoL). Lymphedema can limit mobility and ability to perform daily activities, and have adverse effects on psychological and social wellbeing. When assessing the effect of lymphedema treatment methods, the focus is on change in clinically measured lymphedema status, rather than QoL outcomes. Considering that treatment for lymphedema involves a significant and ongoing commitment from patients, it is essential to determine whether the benefits to patients outweigh the burden associated with treatment. This article summarizes the results of studies assessing the impact of lower-limb lymphedema on QoL in women with gynecological cancer, evaluates their methodologies and discusses limitations and priorities for future research.