Paclitaxel and CYC3, an aurora kinase A inhibitor, synergise in pancreatic cancer cells but not bone marrow precursor cells.

BACKGROUND: Amplification of aurora kinase A (AK-A) overrides the mitotic spindle assembly checkpoint, inducing resistance to taxanes. RNA interference targeting AK-A in human pancreatic cancer cell lines enhanced taxane chemosensitivity. In this study, a novel AK-A inhibitor, CYC3, was investigated in pancreatic cancer cell lines, in combination with paclitaxel. METHODS: Western blot, flow cytometry and immunostaining were used to investigate the specificity of CYC3. Sulforhodamine B staining, time-lapse microscopy and colony-formation assays were employed to evaluate the cytotoxic effect of CYC3 and paclitaxel. Human colony-forming unit of granulocyte and macrophage (CFU-GM) cells were used to compare the effect in tumour and normal tissue. RESULTS: CYC3 was shown to be a specific AK-A inhibitor. Three nanomolar paclitaxel (growth inhibition 50% (GI(50)) 3 nM in PANC-1, 5.1 nM in MIA PaCa-2) in combination with 1 μM CYC3 (GI(50) 1.1 μM in MIA PaCa2 and 2 μM in PANC-1) was synergistic in inhibiting pancreatic cell growth and causing mitotic arrest, achieving similar effects to 10-fold higher concentrations of paclitaxel (30 nM). In CFU-GM cells, the effect of the combination was simply additive, displaying significantly less myelotoxicity compared with high concentrations of paclitaxel (30 nM; 60-70% vs 100% inhibition). CONCLUSION: The combination of lower doses of paclitaxel and CYC3 merits further investigation with the potential for an improved therapeutic index in vivo

Theoretical explanations for maintenance of behaviour change: a systematic review of behaviour theories

Background: Behaviour change interventions are effective in supporting individuals in achieving temporary behaviour change. Behaviour change maintenance, however, is rarely attained. The aim of this review was to identify and synthesise current theoretical explanations for behaviour change maintenance to inform future research and practice. Methods: Potentially relevant theories were identified through systematic searches of electronic databases (Ovid MEDLINE, Embase, PsycINFO). In addition, an existing database of 80 theories was searched, and 25 theory experts were consulted. Theories were included if they formulated hypotheses about behaviour change maintenance. Included theories were synthesised thematically to ascertain overarching explanations for behaviour change maintenance. Initial theoretical themes were cross-validated. Findings: One hundred and seventeen behaviour theories were identified, of which 100 met the inclusion criteria. Five overarching, interconnected themes representing theoretical explanations for behaviour change maintenance emerged. Theoretical explanations of behaviour change maintenance focus on the differential nature and role of motives, self-regulation, resources (psychological and physical), habits, and environmental and social influences from initiation to maintenance. Discussion: There are distinct patterns of theoretical explanations for behaviour change and for behaviour change maintenance. The findings from this review can guide the development and evaluation of interventions promoting maintenance of health behaviours and help in the development of an integrated theory of behaviour change maintenance

Cross-Domain Polarity Models to Evaluate User eXperience in E-learning

[EN] Virtual learning environments are growing in importance as fast as e-learning is becoming highly demanded by universities and students all over the world. This paper investigates how to automatically evaluate User eXperience in this domain using sentiment analysis techniques. For this purpose, a corpus with the opinions given by a total of 583 users (107 English speakers and 476 Spanish speakers) about three learning management systems in different courses has been built. All the collected opinions were manually labeled with polarity information (positive, negative or neutral) by three human annotators, both at the whole opinion and sentence levels. We have applied our state-of-the-art sentiment analysis models, trained with a corpus of a different semantic domain (a Twitter corpus), to study the use of cross-domain models for this task. Cross-domain models based on deep neural networks (convolutional neural networks, transformer encoders and attentional BLSTM models) have been tested. In order to contrast our results, three commercial systems for the same task (MeaningCloud, Microsoft Text Analytics and Google Cloud) were also tested. The obtained results are very promising and they give an insight to keep going the research of applying sentiment analysis tools on User eXperience evaluation. This is a pioneering idea to provide a better and accurate understanding on human needs in the interaction with virtual learning environments and a step towards the development of automatic tools that capture the feed-back of user perception for designing virtual learning environments centered in user's emotions, beliefs, preferences, perceptions, responses, behaviors and accomplishments that occur before, during and after the interaction.Partially supported by the Spanish MINECO and FEDER founds under Project TIN2017-85854-C4-2-R. Work of J.A. Gonzalez is financed under Grant PAID-01-17Sanchis-Font, R.; Castro-Bleda, MJ.; González-Barba, JÁ.; Pla Santamaría, F.; Hurtado Oliver, LF. (2021). Cross-Domain Polarity Models to Evaluate User eXperience in E-learning. 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Usability evaluation of an eHealth intervention for family carers of individuals affected by psychosis: A mixed-method study

Background Existing research suggests that eHealth interventions targeting family carers of individuals with long-term illness offer a promising approach to care delivery. In particular, digital psychoeducational interventions with interactive psychosocial support are well-received with high rates of satisfaction and acceptability. However, development of such interventions for psychosis carers is lacking. We developed a multi-component eHealth intervention specifically for carers of individuals affected by psychosis, called COPe-support (Carers fOr People with Psychosis e-support). Objective Using mixed methods to evaluate usability, system heuristics and perceived acceptability, we conducted a usability study to establish the suitability of the intervention prototype for the target user group. Methods Twenty-three carers were recruited to the study and participated in a think-aloud test or a remote online trial of the intervention. Qualitative feedback, post-use System Usability Scale (SUS) scores, and real-world usage data collected from the tests were analysed. These were also supplemented with heuristic evaluation data provided by an independent eLearning technology expert. Results Participants evaluated the intervention content as useful and helpful, and indicated that the system had satisfactory usability with a mean SUS score of 73%, above the usability quality benchmark threshold. Study results identified some minor usability issues, which were corroborated with the eLearning expert’s heuristic evaluation findings. We used these results to refine the COPe-support intervention. Conclusions The usability study with end-users and service providers identified real-life usage and usability issues. The study results helped us refine COPe-support and its delivery strategy before its launch as part of a large-scale clinical trial

Analyzing collaborative learning processes automatically

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in

Sociological and Communication-Theoretical Perspectives on the Commercialization of the Sciences

Both self-organization and organization are important for the further development of the sciences: the two dynamics condition and enable each other. Commercial and public considerations can interact and "interpenetrate" in historical organization; different codes of communication are then "recombined." However, self-organization in the symbolically generalized codes of communication can be expected to operate at the global level. The Triple Helix model allows for both a neo-institutional appreciation in terms of historical networks of university-industry-government relations and a neo-evolutionary interpretation in terms of three functions: (i) novelty production, (i) wealth generation, and (iii) political control. Using this model, one can appreciate both subdynamics. The mutual information in three dimensions enables us to measure the trade-off between organization and self-organization as a possible synergy. The question of optimization between commercial and public interests in the different sciences can thus be made empirical.Comment: Science & Education (forthcoming

Exploring children’s perspectives on the welfare needs of pet animals

This work was supported by the Department for Environment, Food and Rural Affairs (grant number AW1404).Children are increasingly viewed as important recipients of eduational interventions to improve animal welfare, yet research examining their perspectives is lacking, particularly within the UK. Helping children to care appropriately for animals depends, not least, on an ability to understand the needs of different species and correctly identify cues given by the animal that indicate its welfare state. This study began to explore: (a) children’s perceptions of welfare needs, focusing on four common pet animals; (b) influences on the development of knowledge; (c) beliefs about whether or not (all) animals are sentient, and (d) their confidence in identifying when their own pets are in need. Fourteen focus groups were carried out with 53 children aged 7 to 13 years. Findings highlighted an affirmative response that animals have feelings (dogs especially), albeit with doubts about this applying universally. There was wide variation in children’s knowledge of welfare needs, even among owners of the animal in question. Conversely, some children lacked confidence in spite of the extensive knowledge they had developed through direct experience. An important finding was a perceived difficulty in identifying the needs of particular species or specific types of need in their own pets. Fitting well with a recent emphasis on “positive welfare,” children felt that many animals need demonstrative love and attention, especially cats and dogs. While there is clearly scope for educating children about common needs and cues that indicate animals’ welfare state, other areas pose a greater challenge. Emotional connection seems important in the development of extensive knowledge and concern for welfare. Accordingly, animals that do not possess the kind of behavioral repertoire that is easy to interpret or allows for a perceived sense of reciprocity are possibly at risk of negative welfare experiences.PostprintPeer reviewe

A qualitative study of stakeholders' perspectives on the social network service environment

Over two billion people are using the Internet at present, assisted by the mediating activities of software agents which deal with the diversity and complexity of information. There are, however, ethical issues due to the monitoring-and-surveillance, data mining and autonomous nature of software agents. Considering the context, this study aims to comprehend stakeholders' perspectives on the social network service environment in order to identify the main considerations for the design of software agents in social network services in the near future. Twenty-one stakeholders, belonging to three key stakeholder groups, were recruited using a purposive sampling strategy for unstandardised semi-structured e-mail interviews. The interview data were analysed using a qualitative content analysis method. It was possible to identify three main considerations for the design of software agents in social network services, which were classified into the following categories: comprehensive understanding of users' perception of privacy, user type recognition algorithms for software agent development and existing software agents enhancement

Artificial Intelligence in Government Services: A Systematic Literature Review

The aim of this paper is to provide an overview on how artificial intelligence is shaping the digital era, in policy making and governmental terms. In doing so, it discloses new opportunities and discusses its implications to be considered by policy-makers. The research uses a systematic literature review, which includes more than one technique of data analysis in order to generate comprehensiveness and rich knowledge, we use: a bibliometric analysis and a content analysis. While artificial intelligence is identified as an extension of digital transformation, the results suggest the need to deepen scientific research in the fields of public administration, governmental law and business economics, areas where digital transformation still stands out from artificial intelligence. Although bringing together public and private sectors, to collaborate in the public service delivery, presents major advantages to policy makers, evidence has also shown the existence of negative effects of such collaboration.info:eu-repo/semantics/publishedVersio

"Meaning" as a sociological concept: A review of the modeling, mapping, and simulation of the communication of knowledge and meaning

The development of discursive knowledge presumes the communication of meaning as analytically different from the communication of information. Knowledge can then be considered as a meaning which makes a difference. Whereas the communication of information is studied in the information sciences and scientometrics, the communication of meaning has been central to Luhmann's attempts to make the theory of autopoiesis relevant for sociology. Analytical techniques such as semantic maps and the simulation of anticipatory systems enable us to operationalize the distinctions which Luhmann proposed as relevant to the elaboration of Husserl's "horizons of meaning" in empirical research: interactions among communications, the organization of meaning in instantiations, and the self-organization of interhuman communication in terms of symbolically generalized media such as truth, love, and power. Horizons of meaning, however, remain uncertain orders of expectations, and one should caution against reification from the meta-biological perspective of systems theory