220861 research outputs found
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Comparing and Combining Alternative Strategies for Enhancing Cytochrome P450 Peroxygenase Activity
No full textCytochrome P450 monooxygenase (CYP) enzymes have advantageous properties over chemical catalysts. However, it is often not feasible to use CYPs in larger-scale synthesis as they require additional cofactors (NAD(P)H) and electron transfer proteins. This could be overcome by transforming CYPs into peroxygenases that use H₂O₂. Recently, multiple strategies have been reported for converting CYPs into peroxygenases. Mutating the residues of the acid–alcohol pair in the oxygen-binding groove to those found in natural peroxygenases can promote the desired H₂O₂-driven activity. Another strategy is to enlarge the enzyme’s solvent channels to allow H₂O₂ easier access into the active site, to enhance peroxygenase activity. Here, we evaluate these different strategies by comparing the peroxygenase activities of the double I-helix mutant D251Q/T252E (the QE mutant) and the F182A mutant of the bacterial enzyme CYP199A4. We also assess whether the peroxygenase activity can be further improved by combining these mutations (to give the F182AQE mutant). The F182A mutant exhibited the highest activity toward a selection of smaller substrates that undergo O-demethylation, S-oxidation, and epoxidation reactions. All the mutants converted 4-vinylbenzoic acid into the (S)-epoxide, with the F182A mutant having the highest stereoselectivity (>99% ee). The F182A mutant was unable to oxidize 4-t-butylbenzoic acid, while the F182AQE mutant could with high activity. The F182A mutation was found to substantially alter the selectivity of the reaction with 4-ethylbenzoic acid, increasing hydroxylation activity over desaturation. The F182A mutant catalyzed significant further oxidation reactions of the primary metabolites before all the substrate had been consumed, demonstrating a relaxed substrate specificity. X-ray crystal structures of the F182A and F182AQE mutants with the substrates revealed changes in substrate binding and solvent access providing insights into these experimental observations.Matthew N. Podgorski, Stephen G. Bel
Capacity-building strategy for next-generation mental health research: Embedding a national network infrastructure to grow mental health researcher capabilities and mental health lived-experience research leaders
No full textInternationally, capacity building for mental health implementation and translation research has lagged. A review of literature found initiatives since 2008 indicating limited dedicated attention to growing capabilities of early-to-mid-career mental health researchers, and little reporting of tailored career pathways and skills growth. Significant gaps in capacity building thus exist. This perspective article describes a networked infrastructure for a capacity building strategy of the Australian-based ALIVE National Centre for Mental Health Research Translation. The Centre was funded as a special initiative in mental health with an initial five-year investment. In 2022, the Centre established the first national, cross-disciplinary mental health Next Generation Researcher Network, including a tailored Lived-Experience Research Collective with the aim to grow future research leaders and establish career pathways embedded within the research activities of the Centre. After three years of operation, membership is upward of 280 people in the Next Generation Researcher Network and more than 250 people for the Collective. Specific components implemented as part of the strategy include a central coordination hub, coleadership approaches, coresearch models, tailored traineeships, skills-building through short courses and learning events, cocreation of resources, an online peer discussion platform and annual seed funding schemes. A continuous capacity-building strategy is critical for advancing global research agendas to improve mental health implementation and translation outcomes. Success requires network infrastructure to ensure research methodologies advance, and research addresses the priorities of people most impacted, and early and mid-career researcher capabilities across all research settings connected with universities and service sectors grow.Dana Jazayeri, Michelle Banfield, Caley Tapp, Caroline Tjung, Tegan Stettaford, Victoria Stewart, Giulietta Valuri, Terence Chong, Patricia Cullen, Martina McGrath, Rebecca Cooper, Amanda J Wheeler, Amanda L Neil, Steve Kisely, Jill Bennett, David Preen, Sandra Eades (AO), Lena Sanci, Emma Baker, Victoria J Palme
An implementation of neural simulation-based inference for parameter estimation in ATLAS
No full textPublished 27 May 2025Neural simulation-based inference (NSBI) is a powerful class of machine-learning-based methods for statistical inference that naturally handles high-dimensional parameter estimation without the need to bin data into low-dimensional summary histograms. Such methods are promising for a range of measurements, including at the Large Hadron Collider, where no single observable may be optimal to scan over the entire theoretical phase space under consideration, or where binning data into histograms could result in a loss of sensitivity. This work develops a NSBI framework for statistical inference, using neural networks to estimate probability density ratios, which enables the application to a full-scale analysis. It incorporates a large number of systematic uncertainties, quantifies the uncertainty due to the finite number of events in training samples, develops a method to construct confidence intervals, and demonstrates a series of intermediate diagnostic checks that can be performed to validate the robustness of the method. As an example, the power and feasibility of the method are assessed on simulated data for a simplified version of an off-shell Higgs boson couplings measurement in the four-lepton final states. This approach represents an extension to the standard statistical methodology used by the experiments at the Large Hadron Collider, and can benefit many physics analyses.The ATLAS Collaboratio
A Transcriptome-Wide Mendelian Randomization Study in Isolated Human Immune Cells Highlights Risk Genes Involved in Viral Infections and Potential Drug Repurposing Opportunities for Schizophrenia
No full textFirst published: 24 March 2025Schizophrenia is a neurodevelopmental psychiatric disorder characterized by symptoms of psychosis, thought disorder, and flattened affect. Immune mechanisms are associated with schizophrenia, though the precise nature of this relationship (causal, correlated, consequential) and the mechanisms involved are not fully understood. To elucidate these mechanisms, we conducted a transcriptome-wide Mendelian randomization study using gene expression exposures from 29 human cis-eQTL data sets encompassing 11 unique immune cell types, available from the eQTL catalog. These analyses highlighted 196 genes, including 67 located within the human leukocyte antigen (HLA) region. Enrichment analyses indicated an overrepresentation of immune genes, which was driven by the HLA genes. Stringent validation and replication steps retained 61 candidate genes, 27 of which were the sole causal signals at their respective loci, thereby representing strong candidate effector genes at known risk loci. We highlighted L3HYPDH as a potential novel schizophrenia risk gene and DPYD and MAPK3 as candidate drug repurposing targets. Furthermore, we performed follow-up analyses focused on one of the candidate effectors, interferon regulatory transcription factor 3 (IRF3), which coordinates interferon responses to viral infections. We found evidence of shared genetic etiology between schizophrenia and autoimmune diseases at the IRF3 locus, and a significant enrichment of IRF3 chromatin binding at known schizophrenia risk loci. Our findings highlight a novel schizophrenia risk gene, potential drug repurposing opportunities, and provide support for IRF3 as a schizophrenia hub gene, which may play critical roles in mediating schizophrenia-autoimmune comorbidities and the impact of infections on schizophrenia risk.David Stacey, Liam Gaziano, Preethi Eldi, Catherine Toben, Beben Benyamin, S. Hong Lee, Elina Hyppöne
On Contemporary Chinese Ideology
No full textThis chapter aims to demonstrate that China is not an ideologically aggressive nation that threatens the West. My basic argument is that Chinese leaders post-Mao have been pragmatic in their ideological orientation and sought values and knowledge from three following traditions: traditional Chinese history and culture based on Confucianism, the collective experience of the 1949 Chinese Revolution, and the liberal-capitalist market economy of the Western tradition. My chapter discusses how the post-Mao Chinese leadership, under Xi and his predecessors, has moved among and between these three ideological traditions to guide China’s development. By establishing a connection between these three traditions and China’s development policies, this chapter aims to demonstrate that the Chinese development model, however successful, is NOT based on some monolithic communist ideology. Thus, any argument to justify the West’s decoupling from China based on an autocratic ideology set against democracy or freedom is wrong-headed.Mobo Ga
LGR5: An emerging therapeutic target for cancer metastasis and chemotherapy resistance.
No full textCancer stem cells play an important role in tumor progression and chemotherapy resistance. Leucine-rich G repeat-containing protein-coupled receptor 5 (LGR5) has been identified as a cancer stem cell marker in several cancer types. LGR5 is involved in cancer development and progression via several pathways including WNT/β-catenin signaling pathway. LGR5 plays a role in tumor progression by promoting cancer cell migration, invasion, metastasis, and angiogenesis in many cancers including colorectal, brain, gastric, and ovarian cancer. This review summarises the current knowledge on the expression and functional role of LGR5 in cancers, the molecular mechanisms regulated by LGR5, and the relationship between LGR5 and chemotherapy resistance. The review also includes highlights potential strategies to inhibit LGR5 expression and function. The majority of functional studies have shown that LGR5 plays an important role in promoting cancer progression, metastasis and chemotherapy resistance however, in some contexts LGR5 can also activate tumor-suppressive pathways and LGR5 negative cells can also promote cancer progression. The review highlights that targeting LGR5 is a promising anti-cancer treatment but the functional effect of LGR5 on tumor cells is complex may be dependent on cancer type, tumor microenvironment and cross-talk with other molecules in the LGR5 signaling pathway.Wanqi Wang, Noor A. Lokman, Simon C. Barry, Martin K. Oehler, Carmela Ricciardell
Domain Adaptation Object Detection for Mobile Robots
No full textObject detection is a critical capability for mobile robots navigating diverse and dynamic environments. However, standard methods struggle with domain shifts and real-time adaptability, limiting their deployment in real-world scenarios. To address these challenges, this thesis proposes two novel approaches: an Online Source-Free Domain Adaptation (O-SFDA) framework leveraging unsupervised data acquisition, and an Open-Vocabulary Object Detection (OVOD) model for domain adaptation in embodied environments. The first contribution focuses on improving adaptive object detection using OSFDA by introducing an unsupervised data acquisition framework. In mobile robotics, not all captured frames contain valuable information for adaptation, especially in the presence of strong domain shifts. Our method prioritises the most informative unlabeled samples for inclusion in the online training process, significantly enhancing adaptation performance. Empirical evaluation of real-world datasets demonstrates that this approach surpasses existing state-of-the-art (SOTA) techniques, underscoring the viability of selective data acquisition in improving real-time adaptability. The second contribution leverages OVOD as the base model for domain adaptation in indoor environments. To overcome the limitations of existing methods under domain shifts, we propose a Source-Free Domain Adaptation (SFDA) approach that adapts pre-trained models without requiring access to source data. This approach refines pseudo-labels using temporal clustering, incorporates multi-scale threshold fusion for robust adaptation, and employs a Mean Teacher framework enhanced with contrastive learning. Additionally, we introduce the Embodied Domain Adaptation for Object Detection (EDAOD) benchmark to evaluate performance under sequential changes in lighting, layout, and object diversity. Experimental results highlight substantial improvements in zero-shot detection and adaptability to dynamic indoor conditions, demonstrating the effectiveness of our approach. Together, these contributions advance the SOTA in adaptive object detection for mobile robots, addressing critical challenges posed by domain shifts and dynamic environments. By enabling more robust and flexible object detection, this work facilitates the deployment of mobile robots in real-world scenarios, enhancing their ability to navigate and operate effectively in complex, ever-changing conditions.Thesis (MPhil.) -- University of Adelaide, School of Computer and Mathematical Sciences, 202
Experimental Studies and Stochastic Modelling of Fines Migration in Porous Media during Single and Two-Phase Flow
No full textThis thesis combines visualisation and core-flooding experimental studies to validate particle detachment theory and then combines this theory with distributed particle-rock properties to produce a predictive macroscale detachment model. The model is extended to account for non-spherical particles, the coexistence of multiple particle equilibrium states, particles which form a part of the rock matrix (authigenic particles), and detachment during two-phase flow. Through visualisation studies, this thesis validates the existing model for particle detachment and develops extensions of the theory for particle detachment from both primary and secondary minima. Experiments are conducted with natural clay (kaolinite particles) and oblate spheroidal latex particles and both hydrodynamic and electrostatic force calculations are extended to account for spheroidal particle shapes. A significant gap is observed between the critical detachment velocities for particles in the primary and secondary minima, which allows us to quantify the fraction of particles in each minimum. As a result, a maximum retention function with two-stage detachment process is developed. Additionally, the impacts of the orientation (pitch) angle of particle deposition on electrostatic force, hydrodynamic force, particle deformation, as well as particle detachment are investigated. This thesis addresses a longstanding question of why some experimental studies show that colloids stay attached during drainage experiments, despite theoretical predictions suggesting that they should detach. This is achieved through detailed visualisation observations, traditional torque/force balance calculations, and particle trajectory simulations. This thesis also combines core-flooding experiments and mathematical modelling of colloidal transport to facilitate the construction of a maximum retention function model based on the microscale forces acting on each particle. This is achieved by recognizing the distributions of microscale parameters and constructing a stochastic model for overall detachment. This model is applied for both authigenic and detrital particles. The suite of experimental core-flooding tests conducted as part of this thesis also includes CO₂ injection intended to study formation damage during subsurface gas storage. Intensive fines detachment is observed during the initial CO₂-water displacement stage, while little to no fines production is observed during the evaporation and pure CO₂ flow stages, respectively. As a result, three particle detachment regimes are identified for theoretical consideration: (i) moving CO₂-water interface, (ii) pendular rings underneath the particles, and (iii) pure CO₂ flow. Qualitative agreement is achieved between the modelling and experimental data.Thesis (Ph.D.) -- University of Adelaide, School of Chemical Engineering, 202
Post-translational modification acts as a digital like switch influencing AtPIP2;1 water and cation permeability
No full textPlant aquaporins (AQPs) were initially described as a family of membrane-localized proteins exclusively facilitating water transport. Subsequently, sub-sets of plant AQPs have exhibited diverse functionalities beyond water transport. The aquaporin AtPIP2;1, an abundant Plasma membrane Intrinsic Protein in Arabidopsis thaliana, can transport water but also CO₂, H₂O₂ and monovalent cations under certain conditions. However, the mechanisms regulating the selectivity of AtPIP2;1, particularly for cations and water, remain to be fully explored. Here we report the outcome of mutating four AtPIP2;1 serine phosphorylation sites to mimic states of phosphorylation and dephosphorylation in loops B and D, and the C-terminal domain. Expression of the mutated proteins in Xenopus laevis oocytes allowed analysis of both water and ion conduction. Concurrent modifications at the four phosphorylation sites may collectively act as a ‘selectivity switch,’ modulating the permeability between cations and water for the homotetramer of AtPIP2;1, allowing for the possibility of simultaneous transport, with one substrate remaining dominant. The reciprocal relationship between cation conductance and water transport fits with the model of a gated ion-permeable pore of the tetramer being dependent on the four individual monomer water conductance states. Notably, in several instances, cation conductance can be turned off, reaching levels comparable to those of the H₂O-injected control, and these instances corresponded with maximal water transport. In contrast, when cation conductance was significantly increased, water transport was reduced but not completely silenced. AtPIP2;1 triple mutant S194A/S280DS283D (A/DD, Loop D and C-terminal regions respectively) displayed very high cation conductance with a selectivity sequence for univalent cations of K⁺ > Rb⁺ > Cs⁺ > Na⁺ > Li⁺ > TEA⁺ (tetraethylammonium⁺) > choline⁺ > NMDG⁺ (N-methyl-d-glucamine). In conclusion, our results suggest that post-translational regulations may provide AtPIP2;1 with the flexibility to switch between predominantly cation transport or predominantly water transport. This dynamic ‘switch’ likely contributes to maintaining water and ion homeostasis under diverse environmental conditionsJiaen Qiu, Samantha A. McGaughey, Caitlin S. Byrt, Steve D. Tyerma
Search for boosted low-mass resonances decaying into hadrons produced in association with a photon in pp collisions at root s = 13 TeV with the ATLAS detector
No full textMany extensions of the Standard Model, including those with dark matter particles, propose new mediator particles that decay into hadrons. This paper presents a search for such low mass narrow resonances decaying into hadrons using 140 fb‾¹ of protonproton collision data recorded with the ATLAS detector at a centre-of-mass energy of 13TeV. The resonances are searched for in the invariant mass spectrum of large-radius jets with two-pronged substructure that are recoiling against an energetic photon from initial state radiation, which is used as a trigger to circumvent limitations on the maximum data recording rate. This technique enables the search for boosted hadronically decaying resonances in the mass range 20–100 GeV hitherto unprobed by the ATLAS Collaboration. The observed data are found to agree with Standard Model predictions and 95% confidence level upper limits are set on the coupling of a hypothetical new spin-1 Z′ resonance with Standard Model quarks as a function of the assumed Z′-boson mass in the range between 20 and 200 GeV.ATLAS Collaboratio