RSS 1.0Research from April 2016
This area brings together all research published after April 2016.
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Nance-Horan Syndrome-like 1 protein negatively regulates Scar/WAVE-Arp2/3 activity and inhibits lamellipodia stability and cell migrationCell migration is important for development and its aberrant regulation contributes to many diseases. The Scar/WAVE complex is essential for Arp2/3 mediated lamellipodia formation during mesenchymal cell migration and several coinciding signals activate it. However, so far, no direct negative regulators are known. Here we identify Nance-Horan Syndrome-like 1 protein (NHSL1) as a direct binding partner of the Scar/WAVE complex, which co-localise at protruding lamellipodia. This interaction is mediated by the Abi SH3 domain and two binding sites in NHSL1. Furthermore, active Rac binds to NHSL1 at two regions that mediate leading edge targeting of NHSL1. Surprisingly, NHSL1 inhibits cell migration through its interaction with the Scar/WAVE complex. Mechanistically, NHSL1 may reduce cell migration efficiency by impeding Arp2/3 activity, as measured in cells using a Arp2/3 FRET-FLIM biosensor, resulting in reduced F-actin density of lamellipodia, and consequently impairing the stability of lamellipodia protrusions.
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Deep neural-network prediction for study of informational efficiencyIn this paper, we attempt to verify a hypothesis of informational efficiency of financial markets, known as “random walk” introduced by Fama. Such hypotheses could be considered in relation to financial crises. In our study the hypothesis is tested on data taken from Warsaw Stock Exchange in 2007–2009 years. The hypothesis is tested by predictive modelling based on Machine Learning (ML). We compare conventional ML techniques and the proposed “deep” neural-network structures grown by Group Method of Data Handling (GMDH). In our experiments a GMDH-type neural-network model has outperformed the conventional ML techniques, which is important for achieving the reliable results of predictive modelling and testing the hypothesis. GMDH-type modelling does not require the knowledge of network structure, as a desired network of near-optimal connectivity is learnt from the data. The experimental results compared in terms of prediction error show that the GMDH-type prediction model has a significantly smaller error than the conventional autoregressive and neural-network models.
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Economic development and construction safety research: a bibliometrics approachThe construction industry contributes significantly to economic development worldwide, yet it is one of the most hazardous industries where numerous accidents and fatalities happen every year. Little research to date has shed light on the impact of economic development on construction safety research. In this paper, we conduct an analysis of construction safety articles published in the 21st century via a bibliometrics approach. We have analysed: (1) construction safety in developed and developing countries; (2) the major organisations that have conducted construction safety research; (3) authors and territories of the research and (4) topics in construction safety and future research directions. The largest number of published construction safety documents were published by scholars from the US and China; the total number of published articles by these two countries was 1,125, at 56% of the 2000 articles that were published. Both countries showed high levels of research collaboration. While our results suggest that economic development may drive academic construction safety research, there has been an increase in construction safety research conducted by developing countries in recent years, probably due to an improvement in their economic development. While authors’ keywords evidenced the popularity of research on safety management and climate, the network analysis on all keywords, i.e. keywords given by Web of Science and authors, suggest that construction safety research focused on three areas: construction safety management, the relationship between people and construction safety, and the protection and health of workers’ impact on construction safety. We found that there is a new interdisciplinary research trend where construction safety combines with digital technologies, with the largest number involving deep learning. Other trends focus on machine learning, Building Information Modelling, machine learning and visualisation.
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Memories, mementos, and memorialization of young unaccompanied Afghans navigating within EuropeThis article considers memories, mementos, and memorialization in stories by unaccompanied young people and their journeys within Europe. It looks at their ‘navigation’ of remembering and forgetting and how this intertwines with movement and stillness. It is based on a study about Afghan males aged 15–24 years in Norway and Greece. Participants differed in terms of their backgrounds, migration projects, and their legal status. In their various circumstances, their narratives point to how memories unfold, are shared, must be negotiated, and sometimes, forgotten as they navigate towards a sense of safety and a sustainable future. They also point to how mementos may take different forms while on the move, as traces along the migration trail that have the potential to become part of the memories of others who come across them. Finally, their narratives point to practices of memorialization, and how they too are intimately connected to remembering and forgetting
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Solidarity with Soufra: dividuality and joint action with Palestinian women refugeesBased on an exploratory study of Soufra, a women’s catering social enterprise in the Bourj al Barajneh Palestinian refugee camp in Beirut, we analyse how solidarity across difference can be organized. We conceptualize ‘difference’ not in terms of ‘whole’ individuals, but in terms of dividuals, the multiple roles and social positions that individuals occupy; this enables similarities between individuals of different ethnicities, nationalities and statuses to become apparent. We find that, despite their extreme and protracted marginalization, Soufra does not seek to organize solidarity relationships with co-resisters joining their struggle against oppressors. Rather, they initiate exchange relationships with different others via carefully managed impressions of similar dividualities (e.g. professional cooks and businesswomen) and different dividualities (e.g. having refugee status and lacking any citizenship). These encounters provide opportunities for solidarity relationships to be created and underlying cultural predispositions to be transformed. Whether these opportunities are taken up or rejected is dependent, at least to some extent, on the willingness of participants to allow such transformations to occur.
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Community pharmacists' views on providing a reproductive health service to women receiving opioid substitution treatment: a qualitative study using the TDF and COM-BBackground The absence of menstruation is common in women who use drugs. This can give a belief that conception is unlikely. When stabilised on Opioid Substitution Treatment (OST), fertility often returns, initially without realisation as ovulation precedes menstruation. This leaves women vulnerable to unplanned pregnancies. Community pharmacists (CPs) are frequently in contact with this patient group through the Supervised Consumption of OST service. This provides a timely opportunity to provide reproductive health (RH) advice. The aim of this study was to investigate pharmacists' views on providing a RH service to women receiving OST. Methods Twenty semi-structured interviews based on the Capability-Opportunity-Motivation to Behaviour (COM-B) model and the Theoretical Domains Framework (TDF) were conducted between 2016 and 2017. Data analysis involved deductive coding using the TDF domains. The TDF domains were mapped onto the elements of the COM-B and used in the second step to create the framework and chart the data. The third step involved re-reading and clustering the codes, and inductive themes were generated to explain the data in depth. Results Nine of the 14 TDF domains, mapped into five elements of the COM-B, were identified. Five inductive themes were generated: 1) The pharmacists' experience and knowledge of reproductive health (RH) needs of women receiving OST, 2) The pharmacists' approach to providing advice, 3) The pharmacists' perception of the relationship with women receiving OST, 4) Social influences, and 5) Environmental factors. Community pharmacists feared causing offense to women receiving OST and described requiring cues as to when the service was needed. Pharmacists' highlighted a power imbalance in the relationship with women receiving OST. This could influence how receptive this patient group would be to pharmacy RH interventions. Conclusions CPs' concerns of providing RH service could hinder a proactive service provision. Supporting good rapport and providing a structured consultation would increase the accessibility of such a service.
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Template for Rapid Iterative Consensus of Experts (TRICE)Background: Public health emergencies require rapid responses from experts. Differing viewpoints are common in science, however, “mixed messaging” of varied perspectives can undermine credibility of experts; reduce trust in guidance; and act as a barrier to changing public health behaviours. Collation of a unified voice for effective knowledge creation and translation can be challenging. This work aimed to create a method for rapid psychologically-informed expert guidance during the COVID-19 response. Method: TRICE (Template for Rapid Iterative Consensus of Experts) brings structure, peer-review and consensus to the rapid generation of expert advice. It was developed and trialled with 15 core members of the British Psychological Society COVID-19 Behavioural Science and Disease Prevention Taskforce. Results: Using TRICE; we have produced 18 peer-reviewed COVID-19 guidance documents; based on rapid systematic reviews; co-created by experts in behavioural science and public health; taking 4–156 days to produce; with approximately 18 experts and a median of 7 drafts per output. We provide worked-examples and key considerations; including a shared ethos and theoretical/methodological framework; in this case; the Behaviour Change Wheel and COM-B. Conclusion: TRICE extends existing consensus methodologies and has supported public health collaboration; co-creation of guidance and translation of behavioural science to practice through explicit processes in generating expert advice for public health emergencies.
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The use of objects to enhance online social research interviewsThe ongoing COVID-19 health emergency, and the restrictions that it has placed on research, led many researchers to the re-evaluation of how social research interviews need to go online and how these can be enhanced. The online space presents a platform that brings participants and researchers together in an environment owned by both regardless of who hosts the online session. Online methods are likely to continue through emergencies and crises in general and beyond, and this calls for innovative ways to enhance online research interviews. This chapter discusses a study of a series of online interviews where interviewees were invited to bring an object of personal value with the aim to facilitate a discussion on ‘happiness in lockdown.’ The selected topic served as a vehicle to explore this approach to online interviews while contextualising it in a crisis situation. It also helped to anchor the discussion around a positive theme in the middle of a global crisis. The study aimed at exploring the dynamics observed and the type of thematic materials gathered in this research context. The focus is to investigate the research technique and explore the benefits and challenges of using objects in social research interviews online. As participants select objects related to the research, they are given some control to steer the discussion. Hennigar (1997) discussed the shift in thinking when artefacts are placed at the center of the conversation, and the participant’s own values, beliefs and views about the world could be explored in more depth resulting in what Rubin and Rubin (2012: 95) call an ‘extended conversation.’ The purpose of such a conversation is to explore in depth some themes of relevance to the interviewee through their choice of objects. Using Thematic Analysis (Braun and Clarke, 2006), we explored the richness, depth and genuineness of the materials gathered in object-based online research interviews. The chapter details the research process, discussing the benefits and challenges of using objects as enhancing tools in social research interviews conducted online. It considers how participants chose their items, how the tool compares with other enhancing tools, and some methodological implications. The chapter concludes with our reflection as interviewers offering advice to researchers who may choose to use this enhancing technique in their online interviews.
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Perception of studying dental law and ethics among postgraduate dental students in the UKLaw and ethics is an integral part of medical and dental professional practice. The subject is touched upon in the undergraduate curriculum. Historically, dentists interested in postgraduate study in this subject have accessed courses on medical law and ethics. While there are areas of shared interest (for example, consent, confidentiality) there are differences in emphasis and content (for example, end of life care, organ transplants, etc) which are not relevant to dentistry. A new postgraduate certificate (PgCert) course was approved by the University of Bedfordshire designed specifically for dental practitioners, making it the only university accredited course in the UK that is specific to dental staff. Students' perception of the subject of dental law and ethics at a postgraduate level was not known. The first PgCert student cohort was assessed at the start and the end of the course using two questionnaires. Sixteen students, all qualified dental practitioners working in the UK, took part. The perception toward the subject of dental law and ethics was in-line with the current guideline and regulations governing the dental profession. Perception of dental law was clearer at the end of the course compared to the beginning while dental ethics remained a challenging subject.
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Editorial: How to develop a quality research article and avoid a journal desk rejectionThe desk rejection of submitted articles can be a hugely frustrating and demotivating process from the perspective of the researcher, but equally, a time-consuming and vital step in the process for the Editor, tasked with selecting appropriate articles that meet the required criteria for further review and scrutiny. The feedback from journal Editors within this editorial, highlights the significant gaps in understanding from many academics of the journal assessment process and acceptance criteria for progression to the review stage. This editorial offers a valuable “lived-in” perspective on the desk rejection process through the lens of the Editor, via the differing views of nine leading journal Editors. Each Editor articulates their own perspectives on the many reasons for desk rejection, offering key insight to researchers on how to align their submissions to the specific journal requirements and required quality criteria, whilst demonstrating relevance and contribution to theory and practice. This editorial develops a succinct summary of the key findings from the differing Editor perspectives, offering a timely contribution of significant value and benefit to academics and industry researchers alike.
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Purification and identification of novel xanthine oxidase inhibitory peptides derived from round scad (Decapterus maruadsi) protein hydrolysatesThe objective of the present study was to investigate the xanthine oxidase (XO) inhibitory effects of peptides purified and identified from round scad (Decapterus maruadsi) hydrolysates (RSHs). In this study, RSHs were obtained by using three proteases (neutrase, protamex and alcalase). Among them, the RSHs of 6-h hydrolysis by neutrase displayed the strongest XO inhibitory activity and had an abundance of small peptides (<500 Da). Four novel peptides were purified by immobilized metal affinity chromatography and identified by nano-high-performance liquid chromatography mass/mass spectrometry. Their amino acid sequences were KGFP (447.53 Da), FPSV (448.51 Da), FPFP (506.59 Da) and WPDGR (629.66 Da), respectively. Then the peptides were synthesized to evaluate their XO inhibitory activity. The results indicated that the peptides of both FPSV (5 mM) and FPFP (5 mM) exhibited higher XO inhibitory activity (22.61 +- 1.81% and 20.09 +- 2.41% respectively). Fluorescence spectra assay demonstrated that the fluorescence quenching mechanism of XO by these inhibitors (FPSV and FPFP) was a static quenching procedure. The study of inhibition kinetics suggested that the inhibition of both FPSV and FPFP was reversible, and the type of their inhibition was a mixed one. Molecular docking revealed the importance of π-π stacking between Phe residue (contained in peptides) and Phe914 (contained in the XO) in the XO inhibitory activity of the peptides.
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ABL1 and Cofilin1 promote T-cell acute lymphoblastic leukemia cell migrationThe fusion gene of ABL1 is closely related to tumor proliferation, invasion, and migration. It has been reported recently that ABL1 itself is required for T-cell acute lymphoblastic leukemia (T-ALL) cell migration induced by CXCL12. Further experiments revealed that ABL1 inhibitor Nilotinib inhibited leukemia cell migration induced by CXCL12, indicating the possible application of Nilotinib in T-ALL leukemia treatment. However, the interacting proteins of ABL1 and the specific mechanisms of their involvement in this process need further investigation. In the present study, ABL1 interacting proteins were characterized and their roles in the process of leukemia cell migration induced by CXCL12 were investigated. Co-immunoprecipitation in combination with mass spectrometry analysis identified 333 proteins that interact with ABL1, including Cofilin1. Gene ontology analysis revealed that many of them were enriched in the intracellular organelle or cytoplasm, including nucleic acid binding components, transfectors, or co-transfectors. Kyoto Encyclopedia of Genes and Genomes analysis showed that the top three enriched pathways were translation, glycan biosynthesis, and metabolism, together with human diseases. ABL1 and Cofilin1 were in the same complex. Cofilin1 binds the SH3 domain of ABL1 directly; however, ABL1 is not required for the phosphorylation of Cofilin1. Molecular docking analysis shows that ABL1 interacts with Cofilin1 mainly through hydrogen bonds and ionic interaction between amino acid residues. The mobility of leukemic cells was significantly decreased by Cofilin1 siRNA. These results demonstrate that Cofilin1 is a novel ABL1 binding partner. Furthermore, Cofilin1 participates in the migration of leukemia cells induced by CXCL12. These data indicate that ABL1 and Cofilin1 are possible targets for T-ALL treatment.
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Exercise-induced salivary hormone responses to high-intensity, self-paced runningPhysical overexertion can lead to detrimental overreaching states without sufficient recovery, which may be identifiable by blunted exercise-induced cortisol and testosterone responses. A running test (RPETP) elicits reproducible plasma cortisol and testosterone elevations (in a healthy state) and may detect blunted hormonal responses in overreached athletes. This current study determined the salivary cortisol and testosterone responses reproducibility to the RPETP, to provide greater practical validity using saliva compared with the previously utilized blood sampling. Second, the relationship between the salivary and plasma responses was assessed. A total of 23 active, healthy males completed the RPETP on 3 occasions. Saliva (N = 23) and plasma (N = 13) were collected preexercise, postexercise, and 30 minutes postexercise. Salivary cortisol did not elevate in any RPETP trial, and reduced concentrations occurred 30 minutes postexercise (P = .029, η2 = .287); trial differences were observed (P < .001, η2 = .463). The RPETP elevated (P < .001, η2 = .593) salivary testosterone with no effect of trial (P = .789, η2 = .022). Intraindividual variability was 25% in cortisol and 17% in testosterone. "Fair" intraclass coefficients of .46 (cortisol) and .40 (testosterone) were found. Salivary and plasma cortisol positively correlated (R = .581, P = .037) yet did not for testosterone (R = .345, P = .248). The reproducibility of salivary testosterone response to the RPETP is evident and supports its use as a potential tool, subject to further confirmatory work, to detect hormonal dysfunction during overreaching. Salivary cortisol responds inconsistently in a somewhat individualized manner to the RPETP.
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Working from home during Covid-19: doing and managing technology-enabled social interaction with colleagues at a distanceWith the overnight growth in Working from Home (WFH) owing to the pandemic, organisations and their employees have had to adapt work-related processes and practices quickly with a huge reliance upon technology. Everyday activities such as social interactions with colleagues must therefore be reconsidered. Existing literature emphasises that social interactions, typically conducted in the traditional workplace, are a fundamental feature of social life and shape employees' experience of work. This experience is completely removed for many employees due to the pandemic and, presently, there is a lack of knowledge on how individuals maintain social interactions with colleagues via technology when working from home. Given that a lack of social interaction can lead to social isolation and other negative repercussions, this study aims to contribute to the existing body of literature on remote working by highlighting employees' experiences and practices around social interaction with colleagues. This study takes an interpretivist and qualitative approach utilising the diary-keeping technique to collect data from twenty-nine individuals who had started to work from home on a full-time basis as a result of the pandemic. The study explores how participants conduct social interactions using different technology platforms and how such interactions are embedded in their working lives. The findings highlight the difficulty in maintaining social interactions via technology such as the absence of cues and emotional intelligence, as well as highlighting numerous other factors such as job uncertainty, increased workloads and heavy usage of technology that affect their work lives. The study also highlights that despite the negative experiences relating to working from home, some participants are apprehensive about returning to work in the traditional office place where social interactions may actually be perceived as a distraction. The main contribution of our study is to highlight that a variety of perceptions and feelings of how work has changed via an increased use of digital media while working from home exists and that organisations need to be aware of these differences so that they can be managed in a contextualised manner, thus increasing both the efficiency and effectiveness of working from home.
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Tracking human motion direction with commodity wireless networksDetecting when a person leaves a room, or a house is essential to create a safe living environment for people suffering from dementia or other mental disorders. The approaches based on wearable devices, e.g. GPS bracelets may detect such events require periodic maintenance to recharge or replace batteries, and therefore may not be suitable for certain types of users. On the other hand, camera-based systems require illumination and raise potential privacy concerns. In this paper, we propose a device-free walking direction detection approach based on RF-sensing, which does not require a person to wear any equipment. The proposed approach monitors the signal strength fluctuations caused by the human body on ambient wireless links and analyses its spatial patterns using a convolutional neural network to identify the walking direction. The approach has been evaluated experimentally to achieve up to 98% classification accuracy depending on the environment.
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Time series chlorophyll-A concentration data analysis: a novel forecasting model for aquaculture industryEutrophication in fresh water has become a critical challenge worldwide and chlorophyll-a content is a key water quality parameter that indicates the extent of eutrophication and algae concentration in a body of water. In this paper, a forecasting model for the high accuracy prediction of chlorophyll-a content is proposed to enable aquafarm managers to take remediation actions against the occurrence of toxic algal blooms in the aquaculture industry. The proposed model combines the ensemble empirical mode decomposition (EEMD) technique and a deep learning (DL) long short-term memory (LSTM) neural network (NN). With this hybrid approach, the time-series data are firstly decomposed with the aid of the EEMD algorithm into manifold intrinsic mode functions (IMFs). Secondly, a multi-attribute selection process is employed to select the group of IMFs with strong correlations with the measured real chlorophyll-a dataset and integrate them as inputs for the DL LSTM NN. The model is built on water quality sensor data collected from the Loch Duart salmon aquafarm in Scotland. The performance of the proposed novel hybrid predictive model is validated by comparing the results against the dataset. To measure the overall accuracy of the proposed novel hybrid predictive model, the Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) were used.
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Developing a novel water quality prediction model for a South African aquaculture farmProviding an accurate prediction of water quality parameters for improved water quality management is a topical issue in the aquaculture industry. Conventional prediction methods have shown different challenges like a poor generalization, poor prediction accuracy, and high time complexity. Aiming at these challenges, a novel hybrid prediction model with ensemble empirical mode decomposition (EEMD) and deep learning (DL) long-short term memory (LSTM) neural network is proposed in this paper. In this innovative hybrid EEMD-DL-LSTM model, firstly, the integrity of the datasets is enhanced by applying moving average filtering and linear interpolation techniques of water quality parameter datasets pre-treatment. Secondly, the measured real sensor water quality parameters dataset is decomposed with the aid of the EEMD algorithm into disparate IMFs and a corresponding residual item. Thirdly, a multi-feature selection process is applied to make a careful selection of a strongly correlated group of IMFs with the measured real water quality parameter datasets and integrate them as inputs to the DL-LSTM neural network. The presented model is built on water quality sensor data collected from an Abalone farm in South Africa. The performance of the novel hybrid prediction model is validated by comparing the results against the real datasets. To measure the overall accuracy of the novel hybrid prediction model, different statistical indices, namely the Mean Absolute Error (MAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE), are used.
