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Engineering the Electron Relay in [FeFe]-Hydrogenase Enhances Electrocatalytic H2 Evolution
Get PDFH2 is an ideal energy vector, but catalysts for its clean production from water are inefficient or expensive. [FeFe]-hydrogenases are the most active H2-converting catalysts in nature, using a unique organometallic active site finely tuned by the protein matrix. M3 type [FeFe]-hydrogenases from Clostridium pasteurianum and Clostridium acetobutylicum are exceptionally active for H2 production, and less O2 sensitive than most other types of [FeFe]-hydrogenases, making them attractive targets for biotechnology. However, they are more challenging to work with because of their large size and the number of iron–sulfur clusters. Here, the [FeFe]-hydrogenase from C. acetobutylicum was systematically engineered to truncate each iron–sulfur-containing region of the F-domain, yielding smaller and easier-to-produce catalytic systems. Detailed characterization revealed that these variants retain high electrocatalytic performance and other essential properties of the natural enzyme
A Synthetic Data Generation Pipeline for Improving the Segmentation of Roots in Micro‐CT Images of Soil
Get PDFMachine learning (ML) models for image segmentation typically require a significant amount of accurately annotated data for training, which is rarely readily available in plant and soil science datasets due to the high time and monetary costs of manually labelling the images. Training datasets can be augmented with synthetically generated images that aim to match the visual features and biological properties of the original dataset. Segmentation masks can be created automatically during the synthetic image generation process, removing the need for tedious manual annotation and ensuring high accuracy of the labels. We present an adaptable semi-automatic pipeline for creating annotated synthetic micro-computed tomography (micro-CT) volumes at scale using the 3D modelling tool Blender, and we demonstrate our method using a dataset of micro-CT images of tomato plant roots embedded in sieved soil columns. First, the foreground is generated using a mathematical L-system model to give a 3D model of the target sample. Then, the surrounding material is created and textured to simulate the relative density of the materials in which the object is embedded. The final stage is to render the images by slicing the volume at defined regular intervals, generating both the synthetic micro-CT image and the corresponding labels at each slice. We use our synthetically generated images alongside real data to create augmented datasets to train a U-Net-based segmentation model. Our results demonstrate that when there is a small amount of real annotated data available, using synthetic data in the training dataset can improve the segmentation accuracy, and we show the impact of varying the texturing process
Epistemic Harm: on zemiology and epistemic injustice
No full textZemiology challenges narrow criminological frames in providing frameworks through which social harm can be understood beyond that which is criminalised. It has, though, been relatively inattentive to harms at the epistemic level. Engaging and developing Miranda Fricker’s scholarship, this conceptual/theoretical article produces a concept of epistemic harm, thereby promoting conceptual expansion and theoretical reformulation of zemiology. In turn, this feeds into criminological-zemiological debates regarding central categories for enquiry and their abilities to render social problems recognisable. The applicability of the conceptualisation developed in this article is discussed in relation to examples drawing on race, gender, religion and disability. Through this, the substantive remit of zemiology is expanded: engagement with epistemic harm opens zemiology to a broader arena than it tends to consider currently. Zemiology is also conceptualised as an exercise in epistemic justice itself, which is bolstered through conscious engagement with theory on epistemic justice
Improving the conducting and reporting of veterinary systematic reviews and scoping reviews to facilitate identification and dissemination via the VetSRev database
Get PDFVeterinary medicine advances rapidly, generating extensive amounts of research. Systematic and scoping reviews synthesise evidence to help guide clinical decisions, improve welfare, influence policy, and shape research priorities. Unlike narrative reviews, they employ transparent, rigorous methods. This commentary presents insights from curating VetSRev, a more than a decade-old, freely accessible repository containing an interactive list of published veterinary systematic and scoping reviews. Accessible, high-quality reviews strengthen public and owner trust, improve animal welfare, and promote evidence-based practice. Following established protocols and guidelines ensures quality, visibility, and VetSRev inclusion, thereby disseminating the reviews to users, advancing knowledge, informing research priorities, and enhancing clinical decision-making in veterinary medicine
Termite mound architecture and climate control: a review of X-ray tomography and flow field simulation approaches
Get PDFTermite mounds are known for their ability to maintain self-sustained ventilation and thermoregulation irrespective of external climatic conditions. Although there has been extensive interest in this topic, especially for designing energy-efficient buildings, it is still not fully understood how mound properties are controlled. This article reviews established knowledge and identifies gaps in the study of climate control within termite mounds, proposing an interdisciplinary approach that combines X-ray tomography and flow field simulations. Through specific examples, we demonstrate how these methods can deepen our understanding of termite mound structure and its climate-regulating functions
Mannose Targeting and Hydrophobic Tuning of Polycationic Vectors for Efficient Immunostimulatory CpG Delivery
Get PDFThe efficacy of nucleic acid-based therapeutics is often hindered by nuclease degradation and poor cellular uptake. To address these challenges, the complexation with cationic polymers to form polyplexes has been increasingly investigated. In our previous work, we developed a platform technology composed of a mannosylated block for targeting dendritic cells (DCs) via endocytic mannose receptor (CD206), an agmatinyl block for nucleic acid condensation in diblock copolymers (M15-b-A12, M29-b-A25, and M58-b-A45), elongated with a poly(butyl acrylate) block to promote endosomal escape in triblock copolymers (M29-b-A29-b-B9 and M58-b-A52-b-B32). We exploited these copolymers to efficiently target DCs for cancer vaccination by delivering plasmid DNA encoding tumor-associated antigens (TAAs), using ovalbumin (pOVA) as a model antigen. However, successful T-cell activation requires an antigen presentation on DCs as major histocompatibility complex (MHC)-antigen complexes, along with immune stimulation, making vaccine adjuvants essential. In this study, we utilized mannosylated cationic copolymers to deliver cytosine-phosphate-guanosine oligodeoxynucleotides (CpG ODN) as a vaccine adjuvant and tested their effect in conjunction with pOVA to further enhance immune activation. Cationic glycopolymers efficiently condensed single-stranded DNA (ssDNA), forming stable, predominantly spherical glycoplexes with sizes ranging from 20 to 40 nm, as assessed by transmission electron microscopy (TEM) analysis. These mannosylated complexes showed high internalization by CD206-expressing cells. Confocal laser microscopy studies revealed rapid nuclear localization mediated by M58-b-A52-b-B32 triblock copolymer and slower endosomal escape for M58-b-A45 diblock copolymer-based glycoplexes. Furthermore, for M58-b-A45 diblock copolymer-based complexes, codelivering CpG and pOVA in the same particles induced stronger DC activation compared to coadministration of glycoplexes containing CpG and glycoplexes containing pOVA. These provide a structure–activity relationship for this class of mannosylated cationic glycopolymers for nucleic acid delivery to DCs and underscore the synergistic benefits of codelivering CpG and nucleic acid encoding TAAs for DC activation
Frameworks, theories and models used in the formation and application of health policies: A systematic review of systematic reviews
Get PDFBackgroundHealth policies are established to address a specific health need, however, are not always the result of a rational process of evaluation or developed using established policy frameworks, theories or models (FTMs). Greater utilisation of FTMs in health policy making may provide further insight into policy development and overcome barriers to policy inaction.ObjectiveThe present review aimed to analyse the FTMs and their components underpinning health policy development, and health settings to which they are applied.MethodA systematic review was conducted following the PRISMA guidelines. Several databases were searched using keywords and MeSH terms. Quality appraisal was undertaken using the AMSTAR tool.ResultsFrom 1059 citations, 18 systematic reviews were identified. Twenty-eight FTMs were identified with 15 key components, with policy actors (85 %) and policy context (71 %) being most frequently mentioned. Policy FTMs were applied predominantly in health equity, population and public health (n = 16), sexual, reproductive and women's health (n = 14), HIV (n = 12), and physical activity, obesity prevention and nutrition (n = 12).ConclusionThe utilisation of health policy FTMs in the development of health policy may allow more targeted and relevant health policies to be developed. Further research into the critical components of health policy making may assist in developing a policy framework specific to health policy development
CFD modelling methodology and challenges of hydrogen self-pressurisation and boil-off: A review
Get PDFComputational fluid dynamics (CFD) is widely used in hydrogen technologies to simulate and optimise fluid flow, heat transfer, and safety scenarios across applications such as storage systems, pipelines, fuel cells, and refuelling infrastructure, with the worldwide goal of achieving net-zero and decarbonisation. In this paper, a review of CFD research is presented to assist CFD practitioners in gathering relevant insights to inform their modelling methodology of hydrogen self-pressurisation and boil-off in cryogenic tanks.By examining CFD results from literature, this review explores applicability, resilience and robustness of different models to provide the reader with the best starting point and a clear view of the most suitable CFD route in their specific case. Described multi-phase simulations with conjugate heat transfer include such effects as sloshing, variation of the gravitational acceleration and design modifications to highlight potential impact on the setup, solution and the flow physics. Although the common theme of the studies reviewed here is liquid hydrogen, the principles described can be applied to other cryogenic fluid systems.This review showed that CFD can effectively predict boil-off and self-pressurisation in cryogenic storage. The key findings are that the simulation results are highly sensitive to the fluids thermal properties and boundary conditions, whereas variable coefficients within mass transfer models do not significantly affect the simulation accuracy
A perspective on the interpretability of poverty maps derived from Earth Observation
Get PDFThe use of Earth Observation Data and Machine Learning models to generate gridded micro-level poverty maps has increased in recent years, with several high-profile publications. producing some compelling results. Poverty alleviation remains one of the most critical global challenges. Earth Observation (EO) technologies represent a promising avenue to enhance our ability to address poverty through improved data availability. However, global poverty maps generated by these technologies tend to oversimplify the complex and nuanced nature of poverty preventing progression from proof-of-concept studies to technology that can be deployed in decision making. We provide a perspective on the EO4Poverty field with a focus on areas that need attention. To increase the awareness of what is possible with this technology and reduce the discomfort with model-based estimates, we argue that the EO4Poverty models could and should focus on explainability and operationalizability alongside accuracy and robustness. The use of raw imagery in black-box models results in predictions that appear highly accurate but that are often flawed when investigated in specific local contexts. These models will benefit for incorporating interpretable geospatial features that are directly linked to local context. The use of domain expertise from local end users could make model predictions accessible and more transferable to hard-to-reach areas with little training data
Participatory research in Canada (2013-2018): a cross-sectional survey of academic researchers
Get PDFParticipatory research encompasses diverse investigative approaches that engage community, industry, and other nonacademic collaborators. While investigators have examined single studies to explore research processes and impacts, less is known about the participatory research ecosystem. To address this, our team conducted an online survey to characterize academic researchers who conducted participatory research in Canada (2013–8). Of 1135 respondents (response rate = 27.5 per cent), 38.9 per cent identified their research project as participatory. Results of a multivariable logistic regression showed that academic researchers identifying as women or gender diverse, Indigenous or racialized, of older age, funded by the Social Sciences and Humanities Research Council, and those with larger grants were more likely to conduct participatory research. This study contributes to a growing understanding of individual- and institution-level factors that may influence academic researcher engagement with research coproduction. These findings offer new insights to inform science policy, funding priorities, and sustainable participatory research environments in academia
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