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Observation of quantum effects on radiation reaction in strong fields
No full textRadiation reaction, the force experienced by an accelerated charge due to radiation emission, has long been the subject of extensive theoretical and experimental research. Experimental verification of a quantum, strong-field description of radiation reaction is fundamentally important, and has wide-ranging implications for astrophysics, laser-driven particle acceleration, next-generation particle colliders and inverse-Compton photon sources for medical and industrial applications. However, the difficulty of accessing regimes where strong field and quantum
effects dominate inhibited previous efforts to observe quantum radiation reaction in charged particle dynamics with high significance. We report the first high significance (> 5σ) observation of strong-field radiation
reaction on electron spectra where quantum effects are substantial. We obtain the first, quantitative, strong evidence favouring the quantum-continuous and
quantum-stochastic models over the classical model; the quantum models perform comparably. The lower electron energy losses predicted by the quantum models accounts for their improved performance. Model comparison was performed using a novel Bayesian framework which has widespread utility for laser-particle collision experiments, including those utilising conventional accelerators, where some collision parameters cannot be measured directly
Inhibition of IRAK4 by microbial trimethylamine blunts metabolic inflammation and ameliorates glycemic control
No full textThe global type 2 diabetes epidemic is a major health crisis. Although the microbiome has roles in the onset of insulin resistance (IR), low-grade inflammation and diabetes, the microbial compounds controlling these processes remain to be discovered. Here, we show that the microbial metabolite trimethylamine (TMA) decouples inflammation and IR from diet-induced obesity by inhibiting interleukin-1 receptor-associated kinase 4 (IRAK4), a central kinase in the Toll-like receptor pathway sensing danger signals. TMA blunts TLR4 signalling in primary human hepatocytes and peripheral blood monocytic cells and rescues mouse survival after lipopolysaccharide-induced septic shock. Genetic deletion and chemical inhibition of IRAK4 result in metabolic and immune improvements in high-fat diets. Remarkably, our results suggest that TMA—unlike its liver co-metabolite trimethylamine N-oxide, which is associated with cardiovascular disease—improves immune tone and glycemic control in diet-induced obesity. Altogether, this study supports the emerging role of the kinome in the microbial–mammalian chemical crosstalk
The ENDOMIX project: an interdisciplinary approach to understanding how real-life chemical mixtures target the immune system to trigger disease
No full textThe true impact of endocrine disrupting chemicals (EDCs) on human health is far from being understood. Humans are exposed to mixtures of chemicals throughout their lives, yet regulations and most studies focus on individual chemicals. ENDOMIX takes a novel approach to identifying associations and causality between EDCs and adverse health outcomes by focusing on exposure to mixtures of EDCs over the life course, including windows of susceptibility, using human biomonitoring data from several European cohorts. We will model and measure how real-life EDC mixtures act together and target the immune system to initiate, trigger or maintain disease. Health effects will be investigated using pioneering methodologies ranging from high-throughput in vitro bioassays, sophisticated organoid and co-culture systems, to in vivo models. In combination, they will provide valuable information on mechanistic pathways and transgenerational effects of EDC exposure. We aim to identify biomarkers and patterns of chemical exposures that are easy to measure, available for large cohorts and indicative for adverse health outcomes. We will use in vitro, in silico and in vivo data to strengthen causal inference using a weight-of-evidence approach. Moreover, using novel text mining methods, we will create knowledge graphs to capture and summarize the complexity of biomechanistic information, which aids rapid risk assessments and the creation of network models. The knowledge generated by ENDOMIX will provide an evidence base for policy-making and also reach people of all ages to raise awareness of the risks of EDC exposure and encourage health-promoting behaviors
Infrastructure-led development, urban transformation and inequality in China’s Belt and Road Initiative: a Marxist postcolonial geographies analysis
No full textIn this chapter,1 I aim to explore the intricate connections between infrastructure-led development, urban transformation and inequality within China’s Belt and Road Initiative (BRI). By conceptualizing the BRI as primarily a spatial fix (Harvey, 2016) to the overaccumulation issues inherent in Chinese capitalism, I foreground urbanization as a critical process while considering the dialectical interplay between the territorial and capitalist logics of power (Gramsci, 1971; Harvey, 2005; Lee et al, 2018). Adopting the lens of Marxist postcolonial geographies (Hart, 2006; 2018; Apostolopoulou, 2021a), my goal is to provide a nuanced, relational analysis of diverse trajectories of socio-spatial urban change driven by BRI projects in different cities across the Global South and North with the goal being to understand how the New Silk Road is profoundly reconfiguring the urban geographies of the 21st century
Spatial and temporal patterns of public transit aerobiomes
No full textBackground
Aerobiome diversity is extensive; however, species-level community structure remains poorly resolved. Likewise, microbiomes of public transit systems are of public interest due to their importance for health, though few studies have focused on these ecosystems whilst utilising shotgun metagenomics. Aerosol studies have focused predominantly on individual cities, with limited between-city comparisons suggesting specific community structures. Longitudinal studies show aerobiome diversity as dynamic, fluctuating during seasonal and daily cycles, though interannual cycles remains to be considered. Further, a bacterial bias has limited fungal aerobiome studies, with few considering both fractions collectively. As such, the objective of this study was to examine spatial and temporal patterns in the species diversity of public transit aerobiomes, with an emphasis on bacteria and fungi.
Results
Air samples taken over a 3-year period (2017–2019) from six global cities were subjected to shotgun metagenomic sequencing. Improved classification databases, notably for fungi, applying stringent parameters for trimming, exogenous contamination removal and classification yielded high species-level resolution. Microbial diversity varied substantially among cities, while human and environmental factors, recorded in parallel, were of secondary significance. Bacteria dominated the public transit aerobiome with increased presence in cities with higher population densities. All aerobiomes had complex compositions, consisting of hundreds to thousands of species. Interannual variation had limited significance on the public transit aerobiome diversity and community structure.
Conclusions
Cities were the most important factor contributing to diversity and community structure, demonstrating specific bacterial and fungal signatures. Further, possible correlation between geographical distance and genetic signatures of aerobiomes is suggested. Bacteria are the most abundant constituent of public transit aerobiomes, though no single species is globally dominant, conversely indicating a large inter-city variation in community structure. The presence of a ubiquitous global species core is rejected, though an aerobiome sub-core is confirmed. For the first time, local public transit aerobiome cores are presented for each city and related to ecological niches. Further, the importance of a robust bioinformatics analysis pipeline to identify and remove exogenous contaminants for studying low-biomass samples is highlighted. Lastly, a core and sub-core definition of contaminant aerobiome species with taxon tables, to facilitate future environmental studies, is presented
Aerosol assisted chemical vapor deposition of cobalt-based co-catalysts on bismuth vanadate-based photoelectrodes for solar water splitting systems
No full textCobalt phosphate (CoPi) is a widely used oxygen evolution reaction (OER) catalyst in photoelectrochemical (PEC) water splitting systems. Traditionally, CoPi is fabricated via photo-assisted electrodeposition (PED) from a cobalt-containing electrolyte solution, a method that is limited in scalability. In this study, we demonstrate a novel and scalable route to CoPi, where cobalt oxide (CoOx) is first grown by aerosol-assisted chemical vapor deposition (AACVD) and then surface modified through a dark electrochemical treatment (ET) process. Both fabrication techniques were used to deposit CoPi onto bismuth vanadate (BiVO4) photoanodes synthesised by AACVD. CoPi-decorated BiVO4 fabricated via AACVD + ET demonstrated superior charge separation efficiency, stability over four hours of chronoamperometry, and photoelectrochemical performance, achieving an improved half-cell solar-to-hydrogen (HC-STH) efficiency of 1.16% at 1.23 V vs RHE compared to CoPi-decorated BiVO4 fabricated by PED, which exhibited an HC-STH efficiency of 0.60%. These promising results highlight the potential of AACVD, conducted under atmospheric pressure, to enable the future development of both co-catalysts and scalable photoelectrode fabrication for large-area applications
Application of a contact fatigue life model to assess the relative risk of surface versus subsurface initiated fatigue in gears
No full textThis paper presents a method to assess the relative risk of surface-initiated contact fatigue versus subsurface-initiated fatigue failures under conditions pertinent to gear teeth contacts. The relative risk of surface fatigue is expressed through a parameter SR which is defined as a ratio of near-surface stress integral to total stress integral and calculated using an existing gear fatigue life model. The surface risk parameter is plotted on a failure chart as a function of specific film thickness, Λ and a newly derived surface fatigue criterion, χ which includes effects of surface roughness, Hertz pressure and sliding magnitude on surface fatigue. Parameter χ is expressed as a reciprocal of the well-known plasticity index scaled with applied pressure and slide/rolling ratio. Experimental data is used to validate the predicted chart and identify regions of operating conditions where either micropitting or surface-initiated macropitting or subsurface-initiated spalling are the most likely failure mode. The experimental results are seen to fit well with the trends predicted by the model. The use of new parameter χ together with specific film thickness Λ provides the means for a more comprehensive assessment of the relative risk of micropitting, macropitting and subsurface-initiated spalling in gear teeth contacts than is achievable with simpler parameters. Provided failure charts give an approximate but a simple way to help in assessing the relative risk of surface versus subsurface fatigue failure for a given set of operating conditions
City-wide space-time patterns of environmental noise pollution in Kigali, Rwanda
No full textAs cities in sub-Saharan Africa become more crowded, noise pollution is also emerging as an important environmental concern, after air pollution. Yet, unlike air pollution, which is enjoying relatively more public attention, there is limited measurement data and policy efforts on environmental noise pollution. We followed a recent city-wide measurement approach used in Accra (Ghana) and characterized environmental noise patterns in Kigali, a contrasting city with very different topography and regulatory system than Accra to inform urban policy. We established 10 ‘fixed’ (yearlong) and 120 ‘rotating’ (weeklong) monitoring sites to capture both the temporal and spatial patterns in Kigali’s sound environment. The measurement occurred between November 2022 and December 2023, and samples were collected at 1 min interval, resulting in 5155 014 (3580 site-days) and 1190 620 (827 site-days) site-minutes of valid data from the fixed and rotating sites, respectively. The 130 monitoring sites covered a variety of geographic and land-use factors across diverse neighborhoods and sources. We computed several noise metrics, including 1 h (LAeq1 h), daily (LAeq24 h), day-time (Lday), and night-time (Lnight). Daily noise (LAeq24 h) levels across the city ranged between 38 dBA and 85 dBA. Commercial, business, and industrial (CBI) and high-density residential (HD) communities experienced the highest noise levels, with some sites constantly above 70 dBA at day and 65 dBA at night. About 63% of our observed day-time values (up to ∼72% in some areas) exceeded the Rwandan day-time standard (55 dBA) for residential areas, whereas 69% of the observed night-time values (up to 80% in some areas) exceeded the corresponding night-time standard (45 dBA). In Nyarugenge, the most urbanized district, as much as 75% of our site-days data exceeded day-time standard. However diurnal patterns throughout the city were similar, rising from ∼5 am, peaking at about 8 am and plateauing until 6 pm before falling to their lowest at midnight. Overall, noise levels in the city did not vary much by day of the week, weekdays vs weekend, or dry vs wet seasons. Environmental noise in Kigali often exceeded both Rwandan standards and international guidelines, with residents in the city center district, CBI and HD areas at risk of higher exposure, and hence higher risk of adverse effects. Detailed assessment of the sources, at-risk population, and associated health effects may inform Rwandan’s environmental policy efforts and city initiatives in the face of the ongoing urban growth and densification
What are the current applications of artificial intelligence in point of care ultrasound education?
No full textBackground Point of care ultrasound (POCUS) is an increasingly important clinical skill. The rise of artificial intelligence (AI) in medical imaging offers opportunities to enhance POCUS education, yet access to structured curriculum integrated AI teaching remains limited. This review seeks to explore the application of AI in POCUS education. Methodology A systematic Embase search identified studies evaluating AI in ultrasound education. Inclusion criteria focused on clinical learners and how AI tools were being integrated into their POCUS learning. Thirty-two studies were evaluated using a narrative synthesis method. There was considerable heterogenicity in study design. Findings The highest proportion of studies took place in a perioperative and surgical setting (44%). 47% of the studies evaluated learning outcomes whilst integrating AI tools into the learning program, while the remainder examined applications with educational implications. Four themes emerged from the review: 1. Enhanced anatomical learning through segmentation and highlighting 2. Real time image acquisition guidance 3. Standardised imaging protocols 4. Patient safety during self-directed learning A majority of studies showed improved learner performance, reduced errors or accelerated skill acquisition
Spatial distribution of ectomycorrhizal fungi in Europe
No full textEctomycorrhizal (ECM) fungi play a vital role in temperate and boreal forests by forming symbiotic nutritional relationships with plant roots. Characterising the spatial distribution of ECM fungi, can help understand their habitats and predict their response to global warming. Typically, two types of data are used in ECM fungal studies, data obtained from field observation of fungal specimens (reproductive structures, hereafter fruitbody data) or DNA sequencing data obtained from ECM roots (hereafter root data). In this study, I analysed the environmental niche and geographical distribution of 66 common European ECM fungal species by using biotic and abiotic variables. I assessed how well a single data source could predict the environmental niche of ECM fungi for species with conspicuous (those forming reproductive structures easily visible aboveground) and inconspicuous fruitbodies (those forming reproductive structures not easily visible), and how host plants and global warming influence the geographical distribution of ECM fungi. The results revealed that: 1) at large scale for most species, the environmental niches estimated using either fruitbody data or root data separately had low or medium overlap along environmental gradients, 2) fruitbody data suffice for the niche area estimation of most conspicuous species, but the estimated niche densities (the probability distribution of species in environmental space) were similar when using both data sources, 3) ECM fungal host tree is a main factor in determining ECM fungal geographical distribution, and 4) the distributions of ECM fungi are projected to shift north under future climate change and vary according to their host specificity. This thesis provides contributions to guide the use of data sources as input to understand ECM fungal distributions and could help determine priority areas based on the projected occurrences of species for future sampling and inform the conservation of ECM fungi.Open Acces