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Tetracycline in anaerobic digestion: Microbial inhibition, removal pathways, and conductive material mitigation
No full textTetracycline enters the environment due to its incomplete absorption in humans and animals, posing a significant ecological threat. Tetracycline can hinder the biosystems when treating tetracycline-containing wastewater/waste through anaerobic digestion. This review summarizes the role of tetracycline in inhibiting system performance and related functional microorganisms in holistic process of anaerobic digestion. Tetracycline may primarily inhibit methanogenesis by suppressing acetogenesis, with methane production reductions ranging from 10 % to complete inhibition depending on factors such as tetracycline concentration, inoculum source, substrate composition, and temperature. As a refractory pollutant, tetracycline can be removed in anaerobic digestion systems through adsorption and biodegradation, with removal efficiencies reported between 14.8 % and over 90 %. This review systematically summarizes the mechanisms of tetracycline removal pathways and evaluates the potential contributions. Co-existence of readily biodegradable substrates, extended sludge retention time, and the regulation of environmental parameters such as pH and temperature are potential strategies to enhance tetracycline removal. Moreover, the addition of conductive materials has been identified as a promising strategy to serve as tetracycline adsorbents, facilitate direct interspecies electron transfer and mediate redox reactions, and act as microbial carriers to enhance microbial activity. Finally, this review highlights that the dynamic responses and microbial survival strategies under tetracycline stress deserve further investigation. A deeper understanding of these mechanisms will offer clear theoretical guidance for upgrading technologies for tetracycline-containing wastewater/waste treatment.This research was supported by the Sustainable Energy Authority of Ireland (SEAI; 21/RDD/600). Yuyin Wang thanks the scholarship from the China Scholarship Council (No 202106690004). Guangxue Wu thanks the support from the Galway University Foundation.peer-reviewe
Modelling the non-linear viscoelastic behaviour of brain tissue in torsion
No full textBrain tissue accommodates non-linear deformations and exhibits time-dependent mechanical behaviour. The latter is one of the most pronounced features of brain tissue, manifesting itself primarily through viscoelastic effects such as stress relaxation. To investigate its viscoelastic behaviour, we performed ramp-and-hold relaxation tests in torsion on freshly slaughtered cylindrical ovine brain samples (25 mm diameter and ∼10 mm height). The tests were conducted using a commercial rheometer at varying twist rates of {40, 240, 400} rad m−1 s−1, with the twist remaining fixed at ∼88 rad m−1, which generated two independent datasets for torque and normal force. The complete set of viscoelastic material parameters was estimated via a simultaneous fit to the analytical expressions for the torque and normal force predicted by the modified quasi-linear viscoelastic model. The model's predictions were further validated through finite element simulations in FEniCS. Our results show that the modified quasi-linear viscoelastic model—recently reappraised and largely unexploited—accurately fits the experimental data. Moreover, the estimated material parameters are in line with those obtained in previous studies on brain samples under torsion. These material parameters could enhance our understanding of slow-progressing pathologies such as tumour growth or neurodegeneration and inform the development of improved in silico models for brain surgery planning and training. Our novel testing protocol also offers an efficient, robust and reliable method for determining the viscoelastic properties of brain tissue under much more rapid loading conditions, which are of crucial importance for modelling traumatic brain injury.This publication has emanated from research jointly funded by Taighde Éireann – Research Ireland under grant number GOIPG/2024/3552 (Griffen Small), and by the College of Science and Engineering at the University of Galway under the Millennium Fund scheme for the project “Modelling Brain Mechanics” (Valentina Balbi). Francesca Ballatore acknowledges support from the PNRR M4C2 through the project “Made in Italy Circolare e Sostenibile (MICS)”, CUP: E13C22001900001. The authors are grateful to the anonymous reviewers for their constructive criticisms, helpful suggestions and insights.peer-reviewe
Modelling the time-dependent behaviour of brain tissue in torsion
No full textAs is the case for most biological soft tissues, brain tissue displays highly complex mechanical behaviour: it can accommodate finite deformations and its response to applied forces is markedly non-linear; it is incompressible and biphasic, consisting of a porous permeable solid matrix saturated with an interstitial fluid; it is structurally anisotropic and it exhibits isotropic, time-dependent mechanical behaviour. The latter is one of the most pronounced features of brain tissue, manifesting itself primarily through two distinct but coupled phenomena: poroelasticity and viscoelasticity. The viscoelastic response is associated with the deformation of the solid skeleton, whereas the movement of interstitial fluid through the solid skeleton gives rise to a poroelastic response. Since its coupled poro-viscoelastic behaviour remains only partially understood, brain tissue is typically modelled either as a biphasic poroelastic material or as a monophasic viscoelastic material. The main goal of this work is to use each of these approaches in turn to investigate how poroelastic and viscoelastic effects influence the mechanical behaviour of brain tissue under torsional loading, which is one of the most robust and reliable protocols for determining its material parameters.
Using a biphasic poroelastic model developed within the general framework of mixture theory, we show for the first time computationally that poroelastic effects can significantly influence the torsional response of brain tissue, depending on the loading conditions and the choice of poroelastic material parameters. The sensitivity to these parameters is particularly relevant given the wide range of values reported in the literature. This highlights the need for robust and reliable testing protocols capable of providing a comprehensive and systematic characterisation of the porous behaviour of brain tissue, which is currently lacking in the literature.
Treating brain tissue as a monophasic viscoelastic material, we combine computational and experimental methods to devise the first protocol for determining the viscoelastic material parameters in torsion. From the computational perspective, we develop a monophasic viscoelastic model based on the recently reappraised but largely unexploited modified quasi-linear viscoelastic model. Using a commercial rheometer, we perform ramp-and-hold relaxation tests in torsion on cylindrical brain samples prepared from freshly slaughtered ovine brains, which generates two independent datasets for the torque and normal force. We then use our proposed viscoelastic model to derive analytical expressions for the torque and normal force required to maintain the cylindrical samples in a state of torsion, which allow us to identify the complete set of viscoelastic material parameters through a simultaneous fit to the two datasets. Beyond advancing brain tissue's mechanical characterisation and validating the efficacy of the MQLV model, our results have broader implications. When coupled with bespoke finite element models, the estimated viscoelastic material parameters could enhance our understanding of slow progressing pathologies, such as tumour growth or neurodegeneration, and inform the development of improved in silico models for brain surgery planning and training. Our novel testing protocol also offers an efficient, robust and reliable method for determining the viscoelastic properties of brain tissue under much more rapid loading conditions, which are of crucial importance for modelling traumatic brain injury.Research Ireland (grant number GOIPG/2024/3552), University of Galwa
Developmentally inspired 4D bioprinting of human heart tissue via shape-morphogenesis and in-situ lineage differentiation
No full textBioprinted heart tissues derived from human induced pluripotent stem cells (iPSCs) hold great potential as regenerative implants that can strengthen or replace the failing heart. However, current bioprinting approaches primarily aim to recreate the heart tissue’s end-stage anatomical form, often neglecting the dynamic morphogenetic processes that drive its natural development during embryogenesis. For instance, the heart initially forms as a linear tube that undergoes a series of complex shape transformations, such as looping and chamber formation, that are critical for defining tissue architecture and function. Despite this, existing bioprinting approaches typically utilise static bioinks with minimal capacity for morphogenetic shape changes. As a result, bioprinted heart tissues are structurally and functionally immature compared to their adult counterparts. This immaturity limits their effectiveness as therapeutic implants for heart repair.
The overall objective of this thesis was therefore to bioprint human heart tissues that undergo developmentally inspired shape-morphing and to investigate how these morphogenetic behaviours influence cardiac differentiation and maturation compared to static controls. The central hypothesis was that integrating 4D shape-morphing into the bioprinting workflow would accelerate cell and tissue maturation trajectories.
To achieve this, a 4D bioprinting platform was first developed using collagen and hyaluronic acid bioinks that underwent programmable shape-morphing in granular support hydrogels. Shape-morphing was driven by cell-generated contractile forces and was tunable
via parameters such as cell density, cell type, bioink composition, and support hydrogel viscoelasticity. The geometry of the printed constructs also influenced the extent and nature of morphogenesis, with shape changes arising from mechanical instabilities under endogenous stress. Notably, shape-morphing was found to sculpt cell and extracellular matrix(ECM) alignment along the principal tissue axis through a stress-avoidance mechanism.
Next, it was explored how 4D shape-morphing could impact the structural and functional maturity of human heart tissues derived from iPSCs. Bioprinted heart tissues containing a co-culture of iPSC-cardiomyocytes (iPSC-CMs) and cardiac fibroblasts (7:3 ratio) exhibited enhanced shape-morphing compared to controls composed solely of iPSC-CMs. Notably, fibroblast-mediated shape-morphing enhanced the structural organisation and alignment of iPSC-CMs within the bioprinted heart tissues, resulting in improved contractile properties compared to static controls. Transcriptomic analysis also revealed upregulation of cardiac differentiation markers, including genes encoding sodium ion channels (SCN5A), gap junctions (GJA1, GJA5) and cardiac muscle development (GATA4), confirming enhanced functional maturation.
Building on these results, a developmentally inspired in-situ differentiation strategy was then implemented where bioprinted iPSCs were differentiated into cardiomyocytes within shape-morphing tissue constructs. This approach enabled simultaneous shape-morphing and
lineage specification, as occurs during embryonic heart development. Bioprinted constructs composed of undifferentiated iPSCs were found to maintain pluripotency during early morphogenesis and could then be successfully directed toward mesodermal and cardiac fates
using temporal WNT pathway modulation. The resulting constructs exhibited co-emergence of cardiomyocytes and fibroblast-like cells from a common progenitor population, closely mimicking native developmental processes, and gene expression analysis confirmed
upregulation of early cardiac markers, including TNNI1, NKX2.5, MYH7, and POSTN. Notably, in-situ differentiated constructs exhibited greater structural organisation and cell-cell connectivity compared to those printed with pre-differentiated iPSC-CMs.
In conclusion, this thesis presents a novel strategy for enhancing the structural and functional properties of bioprinted heart tissues by integrating cell-mediated shape-morphing and in-situ differentiation. This developmentally 4D bioprinting framework offers a powerful
platform for engineering organ rudiments that undergo programmable morphogenesis to sculpt their final shape, composition, and function
C3MechLite: An integrated component library of compact kinetic mechanisms for low-carbon, carbon neutral and zero-carbon fuels
No full textBased on our latest detailed chemical reaction mechanism, C3MechV4.0, we have developed two reduced reaction mechanisms—C3MechLite and C3MechCore—targeting C0–C3 chemical species including NH₃. C3MechLite (61 species), contains a number of species comparable to GRI-Mech (53 species), that can accurately predict the combustion characteristics of hydrogen, carbon monoxide, ammonia, methane, natural gas, nitrogen oxides, and their mixtures for a wide range of conditions. C3MechCore (118 species) targets a more comprehensive range of C0–C3 fuels, including ammonia, methanol, ethanol, and dimethyl ether. Both mechanisms demonstrate predictive accuracy comparable to C3MechV4.0 for the combustion characteristics of the target fuels. C3MechLite is designed with a component library structure, enabling further reduction in mechanism size depending on the fuel(s) of interest for 2D/3D numerical simulations. Various combinations of component libraries were validated, and the average prediction error remains within 1 % compared to C3MechLite. Furthermore, the mechanism was applied to 3D LES simulations of H2 lifted flames and was confirmed to reproduce flame characteristics with high accuracy. C3MechLite and its component library structure enable high-fidelity and computationally efficient chemical kinetic mechanisms, paving the way for application in more complex combustion simulations.The authors recognize support from Computational Chemistry LLC, an organization funded by Convergent Science and other industrial members. Q.-D. Wang acknowledges financial support from the National Natural Science Foundation of China (No. 12172335). G.B. and J.B. would like to acknowledge the financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC). The authors at the University of Galway recognize funding from Research Ireland via their Research Centres programme through grant number 12_RC_2302 and project number 16/SP/3829
Deep energy renovations in Irish domestic dwellings: Unlocking health benefits
No full textThe aims of this study were to measure changes in the health of social housing tenants and to estimate indicative health effects associated with changes in exposure to indoor air pollutants (IAPs) following a deep energy retrofit (DER). To this end, a pre–post retrofit design was employed to explore the direct and indirect effects of DER over time, including a health questionnaire completed by residents and indoor air quality measurements in homes. Burden of disease estimates (rate per 100,000) for DER homes were estimated by extrapolating IAP measurements collected pre- and post-retrofit in 14 homes. No changes in health outcomes (i.e. respiratory health and health-related quality of life) or healthcare costs as measured by the questionnaire were observed six months post-retrofit. An increase in median IAP concentrations post-retrofit resulted in an overall net negative effect on health outcomes. Our results demonstrate the importance of occupant behaviours such as tobacco smoking and/or under ventilation (due to blocked wall vents) on exposure to PM2.5 and the resulting health outcomes. The mixed method approach employed to evaluate the impact of DER facilitates a more nuanced understanding of DER's effects.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The HAVEN study was funded by the Sustainable Energy Authority of Ireland under the SEAI Research, Development and Demonstration Funding Programme 2018 (Grant No. 19/RDD/435)
Pastoral power: Perspectives on the present
No full textThis introduction to this special section of Theory, Culture & Society focuses on the formation of power that Michel Foucault – in a number of texts and lectures from the late 1970s and early 1980s – analyzed under the label of ‘the pastorate’. Stressing the ongoing socio-political relevance of pastoral power, the article outlines some of the ways in which it continues to directly influence and animate an array of secular governmental techniques in manners that other critical paradigms can only partially account for. In this, it takes as its focal point two interrelated problematiques: (1) the relation between truth and subjectivity as a constitutive element of modern power relations and (2) the theological subtexts of modern governmentality – demonstrating how they are elaborated upon by the articles comprising the special section
Distinct effects of conductive materials on anaerobic sulfate-rich wastewater treatment under varying operational modes
No full textConductive materials (CMs) have shown great potential in enhancing anaerobic digestion of sulfate-rich wastewater by improving electron transfer. However, how the effectiveness of CMs varies under different reactor operational modes that shape microbial communities and influence system performance remains poorly understood. This study systematically compared sequencing batch reactors (SBRs) and continuous-flow reactors (CFRs) amended with magnetite (Fe₃O₄) or powdered activated carbon (PAC) for treating sulfate-rich wastewater. CM amendments significantly accelerated sulfate reduction, volatile fatty acids degradation, and methane production, especially with the addition of Fe₃O₄. Maximum methanogenesis rates in CFRs increased from 31.2 mg COD/(g VSS·h) without CMs to 51.0 and 39.7 mg COD/(g VSS·h) with the addition of Fe₃O₄ and PAC, respectively. Methanogenesis in SBRs was severely inhibited by elevated hydrogen sulfide concentrations, and supplementation with 1 g/L CMs failed to alleviate this inhibition. CFRs favored direct ethanol-to-acetate conversion, whereas SBRs activated ethanol-to-propionate metabolic pathway mediated by Desulfobulbus. CM additions led to increased sludge conductivity and electron transport activity. Specifically, PAC strongly enhanced electron transfer in CFRs by promoting e-pili and cytochrome gene abundances, whereas Fe₃O₄ in SBRs predominantly acted as an external conductive conduit, partially substituting intrinsic microbial conductive structures. Key sulfate-reducing bacteria (SRB), including Unclassified_f_Desulfovibrionaceae, Desulfomicrobium, Desulfolutivibrio, and Desulfovibrio, dominated the expression of e-pili and cytochrome genes associated with the direct interspecies electron transfer, which was promoted by CFR operation through the enrichment of SRB. Microbial co-occurrence network analysis further highlighted Desulfovibrio, Methanothrix, and Geobacter as central keystone species mediating robust syntrophic electron transfer networks. These findings provide critical insights for optimizing sulfate-rich wastewater treatment through strategic selection of reactor modes and CMs.This study was supported by the Taighde Éireann – Research Ireland (formerly Science Foundation Ireland) and the Sustainable Energy Authority of Ireland under the SFI Frontiers for the Future Awards Programme (22/FFP-A/10346). Wenhui Shu thanks the scholarship from the China Scholarship Council (No: 202106790006). Guangxue Wu thanks for the support from the Galway University Foundation.peer-reviewe
Our Collective Noise (OCN): A tactical response to computer vision, surveillance, and noise
No full textOur Collective Noise (OCN) is a research-based tactical media project. As an attempt to transform the top-down pervasive qualities of machine learning (ML), computer vision (CV), and surveillance technologies into a bottom-up tactical tool, it plays around the concepts of noise, de-identification, accidental aesthetics, and human-machine collaboration. OCN, as an offline system, uses live webcam feed, ML, and CV to detect people and simultaneously turn them into coarse pixels to replace the common aim of precise identification in surveillance technologies with anonymity. Coarse pixels are constantly stitched together to create collective abstract human-machine interaction patterns that people are collectively and unidentifiably part of. In a world where thriving ML, CV, and AI (artificial intelligence) technologies increasingly rely on cleaner datasets, higher processing capacities, precise labels and categories, OCN turns the technology against itself, in pursuit of revealing the latent potential in noise, anonymity, and collective action.Funding for this research is received from the Centre for Creative Technologies, College of Arts, Social Sciences, and Celtic Studies, University of Galway
TCMeta: a multilingual dataset of COVID tweets for relation-level metaphor analysis
No full textThe COVID pandemic spurred the use of various metaphors, some very common and universal, others depending on the language, country and culture. The use of metaphors by the general public, especially in languages other than English, has not yet been sufficiently investigated, one of the reasons being the lack of resources and automatic tools for metaphor analysis. To fill this gap, we introduce TCMeta, a dataset of tweets annotated for metaphors around COVID-19, in two languages from ten different countries. The dataset contains metaphoric phrases covering four source domains. Furthermore, we introduce a semi-automatic methodology to annotate more than 2000 tweets in English and Slovene. To the best of our knowledge, this is the first multilingual semi-automatically compiled dataset of user-generated texts aimed at investigating metaphorical language about the pandemic. It is also the first Slovene dataset of tweets annotated for metaphors.The research leading to these results received funding from Science Foundation Ireland under Grant Number SFI/12/RC/2289_P2 (Insight), and from the Slovene Research Agency (ARRS) under the research core funding P6-0215. The project has also received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 883285. The material presented and views expressed here are the responsibility of the author(s) only. The EU Commission takes no responsibility for any use made of the information set out.peer-reviewe