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Adherent-invasive Escherichia coli in Crohn’s disease:the 25th anniversary.
No full textIn 1998, Arlette Darfeuille-Michaud, Christel Neut and Jean-Frederic Colombel discovered a novel pathovar of Escherichia coli, adherent and invasive Escherichia coli (AIEC), in the ileum of patients with Crohn's disease (CD), that was genetically distinct from diarrheagenic E. coli, could adhere to and invade intestinal epithelial cells and survive in macrophages. The consistent association between AIEC and CD (approximately 30% across the world), their ability to exploit CD-associated genetic traits, and virulence in preclinical colitis models but not healthy hosts spurred global research to elucidate their pathogenicity. Research focused on integrating AIEC with the microbiome, metabolome, metagenome, host response and the impact of diet and antimicrobials has linked the luminal microenvironment and AIEC metabolism to health and disease. This deeper understanding has led to therapeutic trials and precision medicine targeting AIEC-colonised patients. In November 2023, prominent members of the AIEC research community met to present and discuss the many facets of basic, translational and clinical AIEC fields at â AIEC: past, present and future' in NYC. This review is a summary of this international meeting highlighting the history of AIEC, knowledge accumulated over the past 25 years about its pathogenic properties and proposes a standardised approach for screening patients for AIEC.</p
“Open science” meets commercial realities:a qualitative study of factors influencing sharing in synthetic biology research in Australia
Get PDFThis paper examines sharing of data and materials in synthetic biology research and the impact of intellectual property regulation and commercialization imperatives. Data-sharing, access to scientific knowledge, ownership of that knowledge and collaboration are critical issues in biotechnology research, as highlighted in the recent COVID-19 pandemic. We present a sociolegal investigation of drivers of sharing and hindrances to these activities in synthetic biology. This field has a particular emphasis on driving innovation through openness and sharing of the building blocks of research, as opposed to using intellectual property (IP) rights to limit access to these. We examine the perspectives and practices of synthetic biologists in both university and commercial settings, as well as commercialization professionals. We argue that synthetic biologists simultaneously manage two sets of imperatives. On the one hand, sharing is driven by cultural norms, pursuit of scientific progress and strategic benefits to the sharer. On the other, synthetic biologists need to protect their scientific careers, preserve the patentability of developments with commercial potential, and manage obligations to commercial partners and institutions. As their careers may not be purely academic or commercial, they need to appreciate the prerogatives of the particular “hat” that they are wearing on a given project, and also form judgments of commercial value, drawing on a distinction between fundamental and applied research.</p
Safe and unsade e-scooter behaviours in the ACT:Observations and qualitative findings
No full textThis project was funded by the ACT Road Safety Fund Community Grant Program to investigate the factors affecting e-scooter safety in the ACT and provide insights for shaping future safety strategies
Enhancing Upper Limb Exoskeletons Using Sensor-Based Deep Learning Torque Prediction and PID Control
Get PDFUpper limb assistive exoskeletons help stroke patients by assisting arm movement in impaired individuals. However, effective control of these systems to help stroke survivors is a complex task. In this paper, a novel approach is proposed to enhance the control of upper limb assistive exoskeletons by using torque estimation and prediction in a proportional–integral–derivative (PID) controller loop to more optimally integrate the torque of the exoskeleton robot, which aims to eliminate system uncertainties. First, a model for torque estimation from Electromyography (EMG) signals and a predictive torque model for the upper limb exoskeleton robot for the elbow are trained. The trained data consisted of two-dimensional high-density surface EMG (HD-sEMG) signals to record myoelectric activity from five upper limb muscles (biceps brachii, triceps brachii, anconeus, brachioradialis, and pronator teres) during voluntary isometric contractions for twelve healthy subjects performing four different isometric tasks (supination/pronation and elbow flexion/extension) for one minute each, which were trained on long short-term memory (LSTM), bidirectional LSTM (BLSTM), and gated recurrent units (GRU) deep neural network models. These models estimate and predict torque requirements. Finally, the estimated and predicted torque from the trained network is used online as input to a PID control loop and robot dynamic, which aims to control the robot optimally. The results showed that using the proposed method creates a strong and innovative approach to greater independence and rehabilitation improvement.</p
Deep learning based time-dependent reliability analysis of an underactuated lower-limb robot exoskeleton for gait rehabilitation
Get PDFThis study evaluates the reliability of an underactuated wearable lower-limb exoskeleton designed to assist with gait rehabilitation. Recognizing the complexity of system reliability, a deep learning framework augmented with Long short-term Memory (LSTM) was utilized for the time-dependent reliability analysis of dynamic systems. The research commenced with the development of a lower-limb gait robot, modeled on a Stephenson III six-bar linkage mechanism. Following the mechanical design, computer-aided design (CAD) tools were employed to conceptualize a lower-limb robotic exoskeleton for rehabilitation purposes. The design incorporated two metallic materials (aluminum and steel), and a composite material (carbon fiber) tested using SolidWorks ®. The prototype achieved a lightweight design (~1.63 kg) for carbon fiber material. An LSTM-enhanced deep neural network algorithm was implemented to predict the time-dependent reliability of joint displacements and end-effector trajectories. Finally, conditional probability methods were applied to complete the time-dependent system reliability assessment. The designed mechanical system for gait rehabilitation demonstrated high reliability (R ≈ 0.87). Over 200 simulation runs, reliability trends showed consistent and robust predictions.</p
Sex, gender identity and women's health research and equality:An urgent need for clarity of language and accurate data collection
Get PDFBackground: With the rise in salience of the concept of gender identity, changes are being made to language and data collection with major implications for women's health research and equality. Specifically, language referring to women is being desexed and data collection on sex diminishing. In 2023, Australia's National Health and Medical Research Council (NHMRC) undertook public consultations on two draft guidance documents discussing use of the words 'woman'/'women' when describing the involvement of pregnant women in research, and sex and gender identity data collection. We collaborated in writing and gathering support for responses to both consultations. Discussion: We advocated retaining sexed usage of woman/women when sex was relevant, emphasising that addressing sexism and the female data gap requires identifying women as a group and emphasised the need to avoid confusion, dehumanisation, and exclusion of disadvantaged groups. We expressed concern that data collection on gender identity is supplanting that on sex, and sex data is not being accurately collected. We recommended the NHMRC prioritise data accuracy, guide researchers on when and how to collect sex data, and recognise that individuals do not universally apply gender identity to themselves. These issues have international relevance as pressure to desex language and prioritise gender identity data is occurring world-wide. The NHMRC has now finalised its data collection guidance, unfortunately our concerns were largely ignored. Conclusion: Researchers and clinicians globally must urgently participate in policy discussion regarding the importance of sexed language and accurate sex data, to protect individual and population health and data and research integrity.</p
Democratic Assemblage:Power, Normativity, and Responsibility in More-than-Human Participation
Get PDFOver the past two decades, the scholarly community interested in participatory and deliberative democracy has focused their attention on democratic innovations. Designs such as participatory budgets and citizens assemblies have been conceptualised as the actualisation of democratic ideals in a micro setting, in relative isolation from each other and the wider society (Bussu et al. 2022). In recent years the attention of democracy scholarship turned toward the connectivity between various democratic innovations and raised questions about their political and societal impact (Dean et al. 2019; Jaquet et al. 2023; Parry et al. 2021). The deliberative systems approach (Mansbridge et al. 2012) makes important steps towards understanding connectivity by exploring the transmission between public space, where democratic innovations are located, and empowered space, where governments reside (Dryzek 2009). However, both democratic innovations and deliberative systems are too often conceptualised in relatively static terms. Systems imply clear structures, and democratic innovations tend to apply expert-generated design that intends to guide human interaction. This view pays limited attention to the role of materiality and more-than-human world – including physical space, objects, technology, nonhuman animals, weather phenomena, etc. – in democratic participation
“It’s so normalised. Like, yeah, I got another nude today”:image-based online sexual interactions among emerging adults
No full textAs digital technologies continually change, types of negative online behaviours evolve, now covering a wide range of practices, motivations, and behaviours. Research shows that emerging adults are particularly vulnerable to image-based sexual abuse online. However, relatively little is known about emerging adults’ perceptions of and experience with image-based online sexual interactions. This study addresses the gap, focusing on the perception of university students aged 18 to 21, representing early emerging adulthood. The findings reveal that while early emerging adults actively engage in image-based online interactions as part of their socialisation, they also navigate associated risks through boundary negotiation, highlighting the need for open discussions and rights-based education on digital media interactions. The findings of this qualitative study provide important insights into how to approach and view emerging forms of online sexual interactions through a better understanding of how early-stage emerging adults perceive and experience the issue
Beyond ownership:Exploring the sharing economy platforms in Thailand's emerging market
Get PDFDespite the global rise of sharing economy platforms (SEPs), their success in emerging economies remains inconsistent—largely due to institutional voids and the lack of adaptive business models, leaving these platforms particularly vulnerable to external pressures. This study examines the institutional logics influencing SEP development in emerging economies, with Thailand as a case study. Through qualitative analysis, we identify a range of institutional forces and theorize their dynamic influence with platform development. The key insight of our study is the development of a novel integrated interactive sharing economy platform framework that reveals how these external forces act as both enablers and constraints, and how platforms can strategically leverage internal resources and capabilities to balance and contain these pressures. Our findings highlight the critical role of institutional logics in shaping platform outcomes and offer foundational guidance for future research, platform strategy, and policymaking in underexplored institutional contexts, particularly in emerging economies.</p
Financing Arrangements in Public–Private Partnership
No full textPublic–private partnerships (PPPs) are collaborations between public bodies and private entities, structured legally for mutual benefit and geared toward managing state-interest projects over defined periods. Leveraging private capital and expertise, PPPs address global challenges such as ageing infrastructure and budget deficits. This chapter explores diverse financing arrangements within PPPs, assessing their implementation globally across developed and emerging economies. The chapter focuses on optimising financial structures, understanding associated risks, and evaluating variations in financing mechanisms across different economic contexts. The analysis deepens understanding of the financial frameworks supporting PPPs and contributes to the broader discourse on infrastructure development and public service provision