Second messenger pathways in the action of cachectic factors

Cachexia in cancer is characterised by progressive depletion of both adipose tissue stores and skeletal muscle mass. Two catabolic factors produced by cachexia-inducing tumours have the potential for inducing these changes in body composition: (i) proteolysis-inducing factor (PIF) which acts on skeletal muscle to induce both protein degradation and inhibit protein synthesis, (ii) lipid-mobilising factor (LMF), which has been shown to directly induce lipolysis in isolated epididymal murine white adipocytes. Administration of lipid-mobilising factor (LMF) to mice produced a specific reduction in carcass lipid with a tendency to increase non-fat carcass mass. Treatment of murine myoblasts, myotubes and tumour cells with tumour-produced LMF, caused concentration dependent stimulation of protein synthesis, within a 24hr period. It produced an increase in intracellular cyclic AMP levels, which was linearly related to the increase in protein synthesis. The observed effect was attenuated by pretreating cells with the adenylate cyclase inhibitor, MDL12330A and was additive with stimulation produced by forskolin. Both propranolol and a specific 3 adrenergic antagonist SR59230A, significantly reduced the stimulation of protein synthesis induced by LMF. LMF also affected protein degradation in vitro, as demonstrated by a reduction in proteasome activity, a key component of the ubiquitin-dependent proteolytic pathway. These effects were opposite to those produced by PIF which caused both a decrease in the rate of protein synthesis and an elevation on protein breakdown when incubated in vitro.Incubation of LMF with a fat cell line produced alterations in the levels of guanine-nucleotide binding proteins (G proteins). This was also evident in adipocyte plasma membranes isolated from mice bearing the tumour model of cachexia, MAC16 adenocarcinoma and from patients with cancer cachexia. Progression through the cachectic state induced an upregulation of stimulatory G proteins paralleled with a downregulation of inhibitory G proteins. These changes would contribute to the increased lipid mobilisation seen in cancer cachexia.

Maintenance of communication in primary classrooms : some evidence for the role of elicitation and code-switching in English medium schools in Kenya, with implications for teaching

This is a study of specific aspects of classroom interaction primary school level in Kenya. The study entailed the identification of the sources of particular communication problems during the change-over period from Kiswahili to English medium teaching in two primary schools. There was subsequently an examination of the language resources which were employed by teachers to maintain pupil participation in communication in the light of the occurrence of possibility of occurrence of specific communication problems. The language resources which were found to be significant in this regard concerned firstly the use of different elicitation types by teachers to stimulate pupils into giving responses and secondly teachers' recourse to code-switching from English to Kiswahili and vice-versa. It was also found in this study that although the use of English as the medium of instruction in the classrooms which were observed resulted in certain communication problems, some of these problems need not have arisen if teachers had been more careful in their use of language. The consideration of this finding, after taking into account the role of different elicitation types and code-switching as interpretable from data samples had certain implications which are specified in the study for teaching in Kenyan primary schools. The corpus for the study consisted of audio-recordings of English, Science and Number-Work lessons which were later transcribed. Relevant data samples were subsequently extracted from transcripts for analysis. Many of the samples have examples of cases of communication breakdowns, but they also illustrate how teachers maintained interaction with pupils who had yet to acquire an operational mastery of English. This study thus differs from most studies on classroom interaction because of its basic concern with the examination of the resources available to teachers for overcoming the problem areas of classroom communication.

Feature analysis of spammers in social networks with active honeypots:a case study of Chinese microblogging networks

In this poster we presented our preliminary work on the study of spammer detection and analysis with 50 active honeypot profiles implemented on Weibo.com and QQ.com microblogging networks. We picked out spammers from legitimate users by manually checking every captured user's microblogs content. We built a spammer dataset for each social network community using these spammer accounts and a legitimate user dataset as well. We analyzed several features of the two user classes and made a comparison on these features, which were found to be useful to distinguish spammers from legitimate users. The followings are several initial observations from our analysis on the features of spammers captured on Weibo.com and QQ.com. ¦The following/follower ratio of spammers is usually higher than legitimate users. They tend to follow a large amount of users in order to gain popularity but always have relatively few followers. ¦There exists a big gap between the average numbers of microblogs posted per day from these two classes. On Weibo.com, spammers post quite a lot microblogs every day, which is much more than legitimate users do; while on QQ.com spammers post far less microblogs than legitimate users. This is mainly due to the different strategies taken by spammers on these two platforms. ¦More spammers choose a cautious spam posting pattern. They mix spam microblogs with ordinary ones so that they can avoid the anti-spam mechanisms taken by the service providers. ¦Aggressive spammers are more likely to be detected so they tend to have a shorter life while cautious spammers can live much longer and have a deeper influence on the network. The latter kind of spammers may become the trend of social network spammer. © 2012 IEEE.

The representation of food in social media forum Twitter

Social Media is becoming an increasingly important part of people’s lives and is being used increasingly in the food and agriculture sector. This paper considers the extent to which each section of the food supply chain is represented in Twitter and use the hashtag #food. We looked at the 20 most popular words for each part of the supply chain by categorising 5000 randomly selected tweets to different sections of the food chain and then analysing each category. We sorted the users by those who tweeted most frequently and categorised their position in the food supply chain. Finally to consider the indegree of influence, we took the top 100 tweeters from the previous list and consider what following these users have. From this we found that consumers are the most represented area of the food chain, and logistics is the least represented. Consumers had 51.50% of the users and 87.42% of the top words tweeted from that part of the food chain. We found little evidence of logistics representation for either tweets or users (0.84% and 0.35% respectively). The top users were found to follow a high percentage of their own followers with most having over 70% the same. This research will bring greater understanding of how people perceive the food sector and how Twitter can be used within this sector.

Real-time detection, tracking, and monitoring of automatically discovered events in social media

We introduce ReDites, a system for realtime event detection, tracking, monitoring and visualisation. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. Events are automatically detected from the Twitter stream. Then those that are categorised as being security-relevant are tracked, geolocated, summarised and visualised for the end-user. Furthermore, the system tracks changes in emotions over events, signalling possible flashpoints or abatement. We demonstrate the capabilities of ReDites using an extended use case from the September 2013 Westgate shooting incident. Through an evaluation of system latencies, we also show that enriched events are made available for users to explore within seconds of that event occurring.

Who you are or whom you know? Consumption interdependences in social networks

This paper presents an analysis of whether a consumer's decision to switch from one mobile phone provider to another is driven by individual consumer characteristics or by actions of other consumers in her social network. Such consumption interdependences are estimated using a unique dataset, which contains transaction data based on anonymized call records from a large European mobile phone carrier to approximate a consumer's social network. Results show that network effects have an important impact on consumers' switching decisions: switching decisions are interdependent between consumers who interact with each other and this interdependence increases in the closeness between two consumers as measured by the calling data. In other words, if a subscriber switches carriers, she is also affecting the switching probabilities of other individuals in her social circle. The paper argues that such an approach is of high relevance to both switching of providers and to the adoption of new products. © 2013 Copyright Taylor and Francis Group, LLC.

Communication in investigative and legal settings:integrated approaches from forensic psychology, linguistics and law enforcement

Communication in Forensic Contexts provides in-depth coverage of the complex area of communication in forensic situations. Drawing on expertise from forensic psychology, linguistics and law enforcement worldwide, the text bridges the gap between these fields in a definitive guide to best practice. •Offers best practice for understanding and improving communication in forensic contexts, including interviewing of victims, witnesses and suspects, discourse in courtrooms, and discourse via interpreters •Bridges the knowledge gaps between forensic psychology, forensic linguistics and law enforcement, with chapters written by teams bringing together expertise from each field •Published in collaboration with the International Investigative Interviewing Research Group, dedicated to furthering evidence-based practice and practice-based research amongst researchers and practitioners •International, cross-disciplinary team includes contributors from North America, Europe and Asia Pacific, and from psychology, linguistics and forensic practice

Communication in investigative and legal settings:introduction and contexts

Communication in investigative and legal settings is a vitally important area of practice and research. This chapter outlines the significant paradigm shift in interviewing practices, highlighting various studies that have been conducted that have demarked this change. We examine the role of linguistics in this paradigm shift and the importance of training across England and Wales and the Nordic countries in maintaining the professionalization of communication in forensic contexts. The authors outline the significance of maintaining international links across disciplines and summarize the details of each chapter within the book.

Communication in forensic contexts:future directions and conclusions

This chapter reviews the important areas that psychology, linguistics and law enforcement have impacted upon in terms of rigorous and collaborative scientific endeavours. Important areas that will be of interest to both researchers and practitioners for research relating to communication in forensic contexts are discussed in detail, including vulnerability, the use of intermediaries and interpreters in forensic interviews and questioning techniques.

Harnessing linked knowledge sources for topic classification in social media

Topic classification (TC) of short text messages offers an effective and fast way to reveal events happening around the world ranging from those related to Disaster (e.g. Sandy hurricane) to those related to Violence (e.g. Egypt revolution). Previous approaches to TC have mostly focused on exploiting individual knowledge sources (KS) (e.g. DBpedia or Freebase) without considering the graph structures that surround concepts present in KSs when detecting the topics of Tweets. In this paper we introduce a novel approach for harnessing such graph structures from multiple linked KSs, by: (i) building a conceptual representation of the KSs, (ii) leveraging contextual information about concepts by exploiting semantic concept graphs, and (iii) providing a principled way for the combination of KSs. Experiments evaluating our TC classifier in the context of Violence detection (VD) and Emergency Responses (ER) show promising results that significantly outperform various baseline models including an approach using a single KS without linked data and an approach using only Tweets. Copyright 2013 ACM.

An empirical study on uncertainty identification in social media context

Uncertainty text detection is important to many social-media-based applications since more and more users utilize social media platforms (e.g., Twitter, Facebook, etc.) as information source to produce or derive interpretations based on them. However, existing uncertainty cues are ineffective in social media context because of its specific characteristics. In this paper, we propose a variant of annotation scheme for uncertainty identification and construct the first uncertainty corpus based on tweets. We then conduct experiments on the generated tweets corpus to study the effectiveness of different types of features for uncertainty text identification. © 2013 Association for Computational Linguistics.

Exploring demographic information in social media for product recommendation

In many e-commerce Web sites, product recommendation is essential to improve user experience and boost sales. Most existing product recommender systems rely on historical transaction records or Web-site-browsing history of consumers in order to accurately predict online users’ preferences for product recommendation. As such, they are constrained by limited information available on specific e-commerce Web sites. With the prolific use of social media platforms, it now becomes possible to extract product demographics from online product reviews and social networks built from microblogs. Moreover, users’ public profiles available on social media often reveal their demographic attributes such as age, gender, and education. In this paper, we propose to leverage the demographic information of both products and users extracted from social media for product recommendation. In specific, we frame recommendation as a learning to rank problem which takes as input the features derived from both product and user demographics. An ensemble method based on the gradient-boosting regression trees is extended to make it suitable for our recommendation task. We have conducted extensive experiments to obtain both quantitative and qualitative evaluation results. Moreover, we have also conducted a user study to gauge the performance of our proposed recommender system in a real-world deployment. All the results show that our system is more effective in generating recommendation results better matching users’ preferences than the competitive baselines.

Women’s Entrepreneurship: closing the gender gap in access to financial and other services and in social entrepreneurship

This study explores differences between men and women entrepreneurs and social entrepreneurs. It explores the barriers and discriminatory effects that hinder women’s entrepreneurship, including access to finance in the European Union. The study includes four case studies covering the situation in the Czech Republic, Italy, Sweden, and the United Kingdom.