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Cost effectiveness of early metformin in addition to usual care in the reduction of gestational diabetes mellitus effects (EMERGE)—A randomised placebo-controlled clinical trial
No full textAims
To investigate the cost-effectiveness of early initiation of metformin and usual care for gestational diabetes mellitus (GDM).
Methods
Economic evaluation from a healthcare perspective, based on the EMERGE randomised controlled trial. In total, 535 women with GDM were randomised to placebo in addition to usual care or metformin in addition to usual care. Economic outcomes included incremental healthcare costs and quality adjusted life years (QALYs) and expected cost-effectiveness at cost-effectiveness threshold values of €20,000, €45,000 and €100,000 per QALY gained. Uncertainty was explored using parametric, non-parametric, deterministic and probabilistic methods and heterogeneity using subgroup analysis.
Results
On average, relative to the placebo arm, the early metformin arm was associated with non-statistically significant mean increases of €193.07 (95% CI: −€789.88, €1176.01; p = 0.700) and 0.002 QALYs (95% CI: −0.009, 0.013; p = 0.771). In terms of expected cost-effectiveness at threshold values of €20,000, €45,000 and €100,000 per QALY gained, the probability of the early metformin arm being more cost-effective was estimated at 0.423, 0.452 and 0.524. Exploratory subgroup analyses provided more favourable but not definitive evidence in favour of the early metformin arm for cohorts with previous GDM and previous caesarean section.
Conclusions
We do not find definitive evidence that early initiation of metformin in addition to usual care for GDM was more cost-effective than usual care alone. The clinical and economic evidence may be considered equivocal, but worthy of further examination.The trial was funded by the Health Research Board of Ireland, coordinated by the HRB-Clinical Research Facility Galway. Metformin and matched placebo were provided by Merck Healthcare KGaA, Darmstadt, Germany and blood glucose-monitoring strips were provided by Ascensia.peer-reviewe
Coloured shuffle compatibility, Hadamard products, and ask zeta functions
No full textWe devise an explicit method for computing combinatorial formulae for Hadamard products of certain rational generating functions. The latter arise naturally when studying so-called ask zeta functions of direct sums of modules of matrices or class- and orbit-counting zeta functions of direct products of nilpotent groups. Our method relies on shuffle compatibility of coloured permutation statistics and coloured quasisymmetric functions, extending recent work of Gessel and Zhuang.Angela Carnevale was partially supported by the College of Science and Engineering at the University of Galway through a Strategic Research (Millennium) Fund.peer-reviewe
Elastic wave propagation in magneto-active fibre composites
No full textFibre-reinforced elastomers are lightweight and strong materials that can sustain large deformations. When filled with magnetic particles, their effective mechanical response can be modified by an external magnetic field. In the present study, we propose an effective theory of fibre-reinforced composite, based on a neo-Hookean elastic response and a linear magnetic law in each phase. The theory is shown suitable to describe the motion of composite cylinders. Furthermore, it is found appropriate for the modelling of fibre-reinforced composites subjected to a permanent magnetic field aligned with the fibres. To reach this result, we use the incremental theory (‘small on large’), in combination with homogenisation theory and the Bloch–Floquet method. This way, we show that wave directivity is sensitive to the application of a permanent magnetic field, whereas the frequency range in which wave propagation is forbidden is not modified by such a load (the band gaps are invariant). In passing, we describe a method to deduce the total stress in the material based on the measurement of two wave speeds. Furthermore, we propose an effective energy function for the description of nonlinear composites made of Yeoh-type generalised neo-Hookean fibres within a neo-Hookean matrix.This project has received funding from the European Research Council (ERC) through Grant No. 852281 – MAGIC.peer-reviewe
Detecting caste and migration hate speech in low-resource Tamil language
No full textThe Indian constitution categorizes its population into groups such as Scheduled Castes, Scheduled Tribes, Other Backward Classes, and Forward Castes, reflecting historical inequalities that influence social dynamics and discrimination. Migrants who are relocating within the country for better opportunities are often viewed as outsiders, leading to concerns about job security and crime, fostering hate and discrimination against them. Social media has exacerbated these issues, becoming hotspots for caste and migration-related hate speech, especially in low-resource languages. This study introduces a novel dataset specifically curated to detect hate speech related to caste and migration in the low-resourced Tamil language. Using this dataset, we benchmarked the dataset with baseline experiments with the highest macro-F1 score of 0.73. We also created custom-modified models integrating custom loss functions, adapter-based fine-tuning, and parameter-efficient fine-tuning techniques. To support further research, we released the dataset, conducted a shared task, and ranked participant systems. By publicly releasing this dataset, we aimed to facilitate further study and improve the detection and mitigation of hateful content related to caste and migration on social media.peer-reviewe
Mapping the evidence of the effects of environmental factors on the prevalence of antibiotic resistance in the non-built environment
No full textBackground:
Antibiotic resistance increasingly threatens the interconnected health of humans, animals, and the environment. While misuse of antibiotics is a known driver, environmental factors also play a critical role. A balanced One Health approach—including the environmental sector—is necessary to understand the emergence and spread of resistance.
Methods:
We systematically searched English-language literature (1990–2021) in MEDLINE, Embase, and Web of Science, plus grey literature. Titles, abstracts, and keywords were screened, followed by full-text reviews using a structured codebook and dual-reviewer assessments.
Results:
Of 13,667 records screened, 738 met the inclusion criteria. Most studies focused on freshwater and terrestrial environments, particularly associated with wastewater or manure sources. Evidence of research has predominantly focused on Escherichia coli and Pseudomonas spp., with a concentration on ARGs conferring resistance to sulphonamides (sul1–3), tetracyclines (tet), and beta-lactams. Additionally, the People’s Republic of China has produced a third of the studies—twice that of the next country, the United States—and research was largely domestic, with closely linked author networks.
Conclusion:
Significant evidence gaps persist in understanding antibiotic resistance in non-built environments, particularly in marine, atmospheric, and non-agricultural settings. Stressors such as climate change and microplastics remain notably under-explored. There is also an urgent need for more research in low-income regions, which face higher risks of antibiotic resistance, to support the development of targeted, evidence-based interventions.This work was mainly supported by funding from the European Union’s Horizon 2020 Research and Innovation programme under grant agreement No 773830: One Health European Joint Programme (FED-AMR project). This work was also partly co-funded by the European Union’s Horizon Europe Project 101136346 EUPAHW. PK acknowledges the support received from the UK Research and Innovation (UKRI) funded project RECLAIM Network Plus (EP/W034034/1). The funder had no role in the research. For the purpose of Open Access, the author has applied a Creative Commons Attribution (CC BY) public copyright licence to any Author Accepted Manuscript version arising from this submission.peer-reviewe
Evaluating the indoor thermal conditions in a room with a Trombe Wall system: A CFD study
No full textSustainable design and green construction practices are effective solutions to provide comfortable thermal conditions for occupants while decreasing the seasonal heating/cooling demand in buildings. Trombe walls (TWs) are building components that can be used to regulate indoor thermal environment. Utilising TWs as a passive heating and cooling method can help in providing desirable indoor comfort conditions while reducing the reliance on mechanical systems. This study evaluates the indoor thermal conditions in a model room with a TW system. This is done by analysing air temperature and velocity distribution under the defined heat flux values on a TW (200, 250, 300, and 350 W/m²) in both summer and winter conditions typical of Irish weather. Using the grid convergence index (GCI) method to optimize the computational fluid dynamics (CFD) model, the study examines how these heat flux values affect the room conditions in relation to thermal comfort standards.The authors would like to acknowledge the financial support from Science Foundation Ireland (SFI) for the ERBE Centre for Doctoral Training (CDT) under grant agreement no. 18/EPSRC-CDT/3586 and the MaREI Centre under grant agreement no. 12/RC/2302_P2, as well as the Engineering and Physical Sciences Research Council under grant no. EP/S021671/1 for the ERBE CDT. The authors also acknowledge the financial support from the European Union’s Horizon 2020 research and innovation programme under the METABUILDING LABS project (grant agreement no. 953193) and funding from Enterprise Ireland for Construct Innovate, Ireland’s national research centre for construction technology and innovation, under grant agreement no. TC-2022-0033.peer-reviewe
An integrated technoeconomic and environmental assessment of biomethane production via anaerobic digestion of food waste in Ireland: Updated insights under market volatility
No full textThis study presents an integrated techno-economic and environmental assessment of a biomethane plant in Ireland, processing 50,000 tonnes of food waste annually via anaerobic digestion (AD), according to the National Biomethane Strategy. SuperPro Designer simulation was employed to quantify material and energy flows, supporting a techno-economic analysis (TEA) and life cycle assessment (LCA).
The levelized cost of biomethane is estimated at 249 Euro/MWh, 2.9 times the 2019 benchmark, due to high capital (30.3 million Euro) and operational (4.2 million Euro/year) costs driven by inflationary effects caused by external events, such as the war in Ukraine. A biomethane selling price of 111.7 Euro/MWh (household gas price) and gate fees above 69 Euro/tonne are required for breakeven. Unfavourable market conditions would inevitably drive the need for policy supports such as renewable energy incentives or carbon credits to achieve profitability.
The LCA shows a net climate benefit of 46 kgCO2eq/tonne. Still, under-estimated methane leaks could offset these gains and cause revenue losses over 100,000 Euro/year. Digestate circularity following the Nitrates Directive presents trade-offs depending on the impact category.
This integrated analysis reinforces the economic challenges and environmental potential of biomethane production, offering key insights for advancing Ireland’s circular bioeconomy and renewable energy goals.This research was supported by the Department of Agriculture, Food and the Marine (Ireland) (DAFM-2021-R423) and by the Environmental Protection Agency (EPA) of Ireland through the research grant No. 1074
SynAdult: Multimodal synthetic adult dataset generation via diffusion models and neuromorphic event simulation for critical biometric applications
No full textWe propose SynAdult, a multimodal synthetic data generation framework designed to address the scarcity of diverse and privacy-compliant senior adult face datasets for biometric applications and facial analysis. Our pipeline begins with the rendering of high-fidelity 2D adult facial images using parameter-efficient LoRA-based tuning of the state-of-the-art hyperrealism Stable Diffusion XL (SDXL) model, producing photorealistic outputs across diverse ethnicities and age-specific features. Next, we integrate a video retargeting pipeline to synthesize temporally consistent head pose and facial expression sequences, ensuring naturalistic dynamics crucial for downstream video-based facial analysis. In the third stage, we generate neuromorphic event data to introduce a privacy-preserving modality aligned with real-world edge deployment scenarios, such as ambient monitoring and in-vehicle sensing, where high temporal resolution and minimal identity leakage are beneficial. Finally, we reconstruct detailed 3D facial meshes from single 2D frames using 2D-to-3D morphing techniques to capture fine-grained structural details. This modality enhances geometric understanding and supports applications in AR/VR and affective computing. To validate the robustness and utility of the generated dataset, we perform a comprehensive evaluation using Kernel Inception Distance (KID), BRISQUE, CLIP score, and identity similarity metrics. We further assess downstream applicability employing the state-of-the-art facial expression classification networks and event facial landmarks tests for downstream machine learning tasks. As a key contribution, we open-source a large-scale, multimodality, multi-race adult dataset, enabling future research in secure and ethically grounded synthetic data for facial biometrics and facial analysis applications. The project website, along with the complete adult multimodality dataset and the fine-tuned model, is available at https://mali-farooq.github.io/SynAdult/This work was supported in part by the Taighde Eireann–Research Ireland under Grant IRCLA/2023/1992; and in part by the
ADAPT–Centre for Digital Content Technology, Enterprise Ireland.peer-reviewe
Expression and function of new candidate regulators of placodal neurogenesis in Xenopus laevis
No full textThe transcription factor Six1 and its co-activator Eya1 play central and varied roles during the development of sensory neurons derived from the cranial placodes in vertebrates. Previous studies suggested that these proteins promote both the maintenance of proliferative neuronal progenitors and neuronal differentiation. Context-specific interactions of Six1 and/or Eya1 with different cofactors are likely to contribute to the activation of distinct target genes during different stages of placodal neurogenesis. However, while some protein binding partners of Six1 have recently been identified, little is known about Eya1 interaction partners. To uncover additional Eya1 interaction partners with potential roles in placodal neurogenesis, we here conduct a yeast two-hybrid screen in Xenopus laevis. Apart from confirming Six1 (Six1.L) and Six4 (Six4.L and Six4.S) as known protein interaction partners of Eya1, this screen identified 25 additional candidate binding partners including several transcription factors, chromatin modifiers and enzymes involved in posttranslational modifications. Analysis of the expression of genes encoding five of these candidates (garre1, msh6, zmym3, pias4, smarce1) during X. laevis embryogenesis by in situ hybridization, revealed extensive co-expression of each of these with eya1 during placodal development. This suggests potential roles of these candidates in the regulation of placodal neurogenesis possibly in conjunction with Eya1. In gain and loss of function studies of the E3 SUMO-ligase Pias4 and the chromatin modifier Smarce1, we confirm essential roles of both of these proteins for placodal neurogenesis but their mode of interaction with Eya1 remains to be further clarified.This study was funded by Research Ireland (Frontiers for the Future grant 19/FFP/6679) and a University of Galway College of Science scholarship for Bertrand Hutlet
Numerical wave tank development for hydrodynamic analysis of a tidal turbine
No full textTidal energy can play an important part in balancing the world’s electricity grid, considering its enormous potential and advantages of reliability and predictability. Many existing studies show that tidal turbines experience frequent and large scale load fluctuations when effected by ocean waves, which may lead to blade fatigue damage. Therefore, in this paper, a computational fluid dynamics wave tank model, based on an existing physical wave tank, is developed, with calibrated wave parameters as the input wave profile, to evaluate the hydrodynamic performance of turbines in conditions influenced by waves.This research was funded in part by Science Foundation Ireland (SFI) through the MaREI Research Centre for Energy, Climate and Marine (Grant no. 12/RC/2302_2) and the European Com mission through the H2020 CRIMSON project (grant agreement no.: 971209)