Delineating breast cancer cell interactions with engineered bone microenvironments

The mechanisms leading to colonization of metastatic breast cancer cells (BCa) in the skeleton are still not fully understood. Here, we demonstrate that mineralized extracellular matrices secreted by primary human osteoblasts (hOBM) modulate cellular processes associated with BCa colonization of bone. A panel of four BCa cell lines of different bone-metastatic potential (T47D, SUM1315, MDA-MB-231, and the bone-seeking subline MDA-MB-231BO) was cultured on hOBM. After 3 days, the metastatic BCa cells had undergone morphological changes on hOBM and were aligned along the hOBM's collagen type I fibrils that were decorated with bone-specific proteins. In contrast, nonmetastatic BCa cells showed a random orientation on hOBM. Atomic force microscopy-based single-cell force spectroscopy revealed that the metastatic cell lines adhered more strongly to hOBM compared with nonmetastatic cells. Function-blocking experiments indicated that β1-integrins mediated cell adhesion to hOBM. In addition, metastatic BCa cells migrated directionally and invaded hOBM, which was accompanied by enhanced MMP-2 and -9 secretion. Furthermore, we observed gene expression changes associated with osteomimickry in BCa cultured on hOBM. As such, osteopontin mRNA levels were significantly increased in SUM1315 and MDA-MB-231BO cells in a β1-integrin-dependent manner after growing for 3 days on hOBM compared with tissue culture plastic. In conclusion, our results show that extracellular matrices derived from human osteoblasts represent a powerful experimental platform to dissect mechanisms underlying critical steps in the development of bone metastases.

The TFOS International Workshop on Contact Lens Discomfort: report of the contact lens interactions with the ocular surface and adnexa subcommittee

The report of this subcommittee concerns the impact of contact lenses (CLs) on the ocular surface, with a particular emphasis on CL discomfort (CLD). We define the ocular surface, its regional anatomy, and the physiological responses of each region to CL wear.

Going online : young children and teachers accessing knowledge through web interactions

Children accessing and using internet-connected technology is a relatively recent phenomenon, and rapidly having an impact on their experiences and activities in homes and early childhood classrooms. Technology refers to devices such as computers, smart phones and tablets - many capable of being connected to the internet - and the products, such as websites, games, and interactive stories (Plowman and McPake, 2013). These activities can be played, created, watched, listened to and read, and incorporated into traditional everyday activities. This article provides suggestions for strategies for teachers to consider when incorporating technology into early childhood education.

A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation technology. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches consider the energy consumption by physical machines only, but do not consider the energy consumption in communication network, in a data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement. In our preliminary research, we have proposed a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both physical machines and the communication network in a data center. Aiming at improving the performance and efficiency of the genetic algorithm, this paper presents a hybrid genetic algorithm for the energy-efficient virtual machine placement problem. Experimental results show that the hybrid genetic algorithm significantly outperforms the original genetic algorithm, and that the hybrid genetic algorithm is scalable.

Mathematical investigation of the interactions between the inflammatory response and mechanical aspects of dermal wound repair

Dermal wound repair involves complex interactions between cells, cytokines and mechanics to close injuries to the skin. In particular, we investigate the contribution of fibroblasts, myofibroblasts, TGFβ, collagen and local tissue mechanics to wound repair in the human dermis. We develop a morphoelastic model where a realistic representation of tissue mechanics is key, and a fibrocontractive model that involves a reasonable approximation to the true kinetics of the important bioactive species. We use each of these descriptions to elucidate the mechanisms that generate pathologies such as hypertrophic scars, contractures and keloids. We find that for hypertrophic scar and contracture development, factors regulating the myofibroblast phenotype are critical, with heightened myofibroblast activation, reduced myofibroblast apoptosis or prolonged inflammation all predicted as mediators for scar hypertrophy and contractures. Prevention of these pathologies is predicted when myofibroblast apoptosis is induced, myofibroblast activation is blocked or TGFβ is neutralised. To investigate keloid invasion, we develop a caricature representation of the fibrocontractive model and find that TGFβ spread is the driving factor behind keloid growth. Blocking activation of TGFβ is found to cause keloid regression. Thus, we recommend myofibroblasts and TGFβ as targets for clinicians when developing intervention strategies for prevention and cure of fibrotic scars.

Understanding the implications of digital interactions on the design of public urban spaces

This study investigated the impact of digital networked social interactions on the design of public urban spaces. Urban informatics, social media, ubiquitous computing, and mobile technology offer great potential to urban planning, as tools of communication, community engagement, and placemaking. The study considers the function of public spaces as 'third places,' that is, social places that are familiar, comfortable, social and meaningful for everyday life outside the home and work. Libraries were chosen as the study's focus. The study produced findings and insights at the intersection of urban planning (place), cultural geography and urban sociology (people), and information communication technology (technology) – the triad of urban informatics.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

Automatic classification of free-text radiology reports to identify limb fractures using machine learning and the SNOMED CT ontology

Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

Organizational probes : exploring playful interactions in work environment

Playfulness, with non-intrusive elements, can be considered a useful resource for enhancing social awareness and community building within work organizations. Taking inspirations from the cultural probes approach, we developed organizational probes as a set of investigation tools that could provide useful information about employees’ everyday playful experiences within their work organizations. In an academic work environment, we applied our organizational probes over a period of three weeks. Based on the collected data we developed two design concepts for playful technologies in work environments.

Exploring mediated interactions : a design exercise

With the emergence of personal and ubiquitous computing systems in the last decade, interaction designers have started designing products by employing quality oriented aspects such as user experience, playfulness, enchantment and others. In order to explore novel forms of mediated interactions, designers need to focus beyond the basic user requirements and usability issues. We present a procedure and results of a design exercise that we carried out with students of a master's course on Visual Design. Our intention was to explore new forms of mediated interaction by using a specific design exercise. We provide the details of the resulted design concepts and discuss the usefulness of our design exercise.

Aesthetics of mundane interactions

John Dewey’s pragmatist aesthetics is used as a conceptual basis for designing new technologies that support staff-members’ mundane social interactions in an academic department. From this perspective, aesthetics is seen as a broader phenomenon that encompasses experiential aspects of staffmembers’ everyday lives and not only a look-&-feel aspect.

Interactions between organizational culture, trustworthiness, and mechanisms for inter-project knowledge sharing

This research used a multiple-case study approach to empirically investigate the complex relationship between factors influencing inter-project knowledge sharing—trustworthiness, organizational culture, and knowledge-sharing mechanisms. Adopting a competing values framework, we found evidence of patterns existing between the type of culture, on the project management unit level, and project managers’ perceptions of valuing trustworthy behaviors and the way they share knowledge, on the individual level. We also found evidence for mutually reinforcing the effect of trust and clan culture, which shape tacit knowledge-sharing behaviors.