220861 research outputs found
Sort by
Endoscopic ultrasound molecular evaluation of pancreatic cancer trial to profile molecular landscape of inoperable pancreatic ductal adenocarcinoma
No full textBackground and study aims Pancreatic ductal adenocarcinoma (PDAC) is a poor prognostic malignancy. Comprehensive genomic profiling (CGP) has improved outcomes in many cancers, but widespread uptake in PDAC remains elusive. This study investigated the feasibility of using endoscopic ultrasound with fine-needle biopsy (EUS-FNB) for CGP in advanced PDAC. Patients and methods (experimental design) A multicenter prospective cohort study was conducted to assess the feasibility of using DNA and RNA extracted from fresh frozen or archival formalin-fixed paraffin-embedded (FFPE) EUS-FNB for CGP on advanced PDAC using the TSO-500 gene panel testing. Results of the CGP were reviewed at a molecular tumor board (MTB) and subsequent treatment recommendations were forwarded to the referring clinicians. Results CGP was successful in 129 of 143 patients (90%) enrolled between May 2020 to September 2023. Fresh frozen EUS-FNB provided suitable genetic material for CGP in 123 of 133 patients (92%). Conversely, CGP was successful on FFPE biopsy blocks from only six of 16 patients (38%). Fifty-two of 143 patients (36%) had a potentially targetable mutation detected, and eight of these patients (6%) were treated with targeted therapy based on their EUS-FNB-derived molecular profile. Patients who received personalized therapy had a significant (P 18 months for personalized therapy. Conclusions This real-world study confirms the feasibility and utility of CGP using EUS-FNB in advanced PDAC. It illustrates the importance of timely access to personalized therapy informed by CGP, which can impact the treatment pathway and improve survival outcomes.Owen McKay, Joanne Lundy, Sally Bell, Phil Ha, Hugh Gao, Brendan Jenkins, Chamkaushalya Bulathsinghalage, Michael Swan, Simon Hew, Belinda Lee, Pranav Dorwal, Manoop S Bhutani, Vivek Rathi, Sean Grimmond, Andrew Perry, TrevorWilson, Andrew Strickland, John Zalcberg, Daniel Croag
Strength reduction of crumb rubber concrete: microstructures and mesoscale modelling
No full textLink to a related website: https://orcid.org/0000-0002-0954-3541, ORCID profile - Chen, HuailiangThis paper presents a mesoscale model to investigate the rubber particle effect on the compressive strength of crumb rubber concrete (CRC) through considering varying rubber particle contents, particle sizes, distributions, and shapes. The mesoscale model was simulated through a five-phase internal structure composed of rubber particle, coarse aggregate, mortar, coarse aggregate-mortar interfacial transition zone (A-M ITZ), and rubber particle-mortar interfacial transition zone (R-M ITZ). The modulus of R-M ITZ and A-M ITZ were 41 %-58 % and 70 %-85 % of the mortar phase with corresponding thickness of 30–70 µm and 30–60 µm, respectively, as measured from nanoindentation tests. Mesoscale modelling was carried out on 100×200 mm CRC cylinder samples with 6 %-18 % rubber percentage by sand volume and compared with the average results of three tested samples. The parametric analysis indicated that the rubber content was the main factor affecting the strength reduction of CRC. The effect of ITZ on the CRC strength was relatively low and negligible. Rubber particle size effect was evaluated through analysing CRC samples with three different rubber sizes, i.e., 1.77 mm, 3 mm, and 7 mm. For each size, six CRC models containing different rubber particle distributions were generated. CRC models with the same rubber content presented similar average compressive strengths even though with rubber particles of varied sizes. However, larger rubber particle size increased the strength variation among CRC models. Further simulation showed that replacing the rubber particles in the CRC with the same content of pores did not change compressive strength or the damage pattern of the CRC samples. Finally, a prediction formula for strength reduction rate of CRC in terms of rubber content was developed. The numerical results were in good agreement with experimental tests in the current study and previous studies from literature
Systematic review of physical, mechanical and durability performances of metakaolin concrete
No full textThe growing emphasis on environmental sustainability has significantly boosted research into metakaolin (MK)-based concrete as a viable alternative to traditional cement. The incorporation of MK enhances the mechanical and microstructural properties of concrete. Furthermore, it improves specific durability aspects, including chloride resistance, reduced permeability, and increased resistance to acid and alkali attacks. The overall enhancements arise from the small particle size's fill effect, improving packing density, and the pozzolanic reaction that produces additional gels, resulting in stronger and more durable concrete. However, the literature reveals mixed results concerning other durability factors, particularly carbonation resistance, water absorption, and shrinkage behaviour. Previous studies have indicated that a 10 % replacement reduced carbonation depth, and a 15 % MK dosage decreased capillary water absorption. In contrast, other investigations have highlighted potential drawbacks, including an increase in carbonation depth at 10–15 % MK replacement, a substantial dry shrinkage beyond 15 %, and greater water absorption at higher replacement levels. This review paper identifies and outlines research gaps in understanding how the structure of raw kaolinite influences its pozzolanic reactivity, mechanical performance, and durability properties in green concrete. The review paper consolidates key research findings on metakaolin, highlighting its durability properties as a partial replacement for cement, with an optimal level of 10–15 % MK in concrete
Shear behaviour of SWSS-SCC deep beams reinforced with GFRP longitudinal bars and CFRP strip stirrups
No full textAlthough fibre-reinforced polymer (FRP) is widely used as a substitute for steel reinforcement in concrete structures, post-pultrusion bending of FRP bars leads to significant performance deficiency in the bending zone. This study adopted flexible carbon FRP (CFRP) strips as stirrups to investigate the shear behaviour of seawater sea-sand self-compacting concrete (SWSS-SCC) deep beams reinforced with glass FRP (GFRP) bars. Nine full-scale beams were tested to shear failure, with variables including beam depth (350 mm, 450 mm, 600 mm), CFRP strip stirrup ratio (0 %, 0.05 %, 0.11 %, 0.16 %), and shear span-depth ratio (1.5, 2.0). All beams exhibited shearcompression failure, and the nominal shear strength decreased approximately linearly with increasing beam depth, confirming the presence of a size effect. Increasing beam depth from 350 mm to 600 mm reduced the nominal shear strength by 23 % in stirrup-free beams and by only 13 % in beams with CFRP strip stirrups, indicating that CFRP strip stirrups effectively mitigate but cannot completely eliminate the size effect. A modified shear design equation was proposed, considering the size effect, effective strain of CFRP strips at failure, and the arching effect of deep beams. Validation results demonstrate that the proposed equation can accurately predict the shear capacity of SWSS-SCC deep beams reinforced with CFRP strip stirrups, with an average experimentalto-predicted ratio of 1.02
Refining capsaicin-induced pain models: A comprehensive analysis of preclinical practices and their translational potential
No full textPain remains a significant clinical challenge despite advances in mechanistic understanding. Animal models have been instrumental in advancing our understanding of pain mechanisms, however translating this understanding into positive clinical outcomes has been lacking. Capsaicin, a TRPV1 agonist and active component of chili peppers, is widely used in pre-clinical pain studies to evoke nociceptive responses. This systematic review investigates how capsaicin is currently used as a nociceptive stimulus in preclinical behavioural models of pain. We examine the purpose of capsaicin use, species and sexes of animals tested, methods of administration, dosage, and the types of pain behaviours assessed. Capsaicin-evoked behaviours are primarily used to understand TRPV1 specific pain mechanisms and screen analgesic compounds. We report male rodent studies are the dominant subject for capsaicin-induced behaviours and that within the limited studies involving female rodents, conflating data regarding sex specific effects exists. Very few novel behavioural techniques have been introduced, with studies heavily relying on behavioural measures such as von Frey sensitivity, hindpaw movements and thermal withdrawal latencies. We also report no significant correlation between increasing capsaicin dose and time of observed behavioural sensitivity, suggesting lower doses should be considered. We believe the data collected and reported here is useful to future researchers in both assessment of model relevance and informing experimental design. By analysing current practices and identifying areas for improvement in experimental design, this review aims to inform methodology for future studies and improve animal welfare.Samuel G. Evans, Femke T.A. Buisman-Pijlman, Sanam Mustafa, Mark R. Hutchinso
Recovery of magnesite from silicate gangue minerals via reverse flotation using a novel alkyl ether amine collector
No full textMagnesite (MgCO3) has wide applications in industries including refractories, building materials and environmental remediation. However, magnesite applications may be limited due to common association with gangue minerals such as quartz and other silicate minerals (talc) which need to be removed in order to produce a highgrade magnesite concentrate. The removal of silicate gangue minerals is a long-standing challenge in magnesite ore beneficiation, particularly using froth flotation and collectors display mediocre selectivity. In the quest for more efficacious collector for flotation to separate quartz (SiO2) and talc (Mg3Si4O10(OH)2) from magnesite, a novel alkyl ether amine collector was studied in a three-stage reverse flotation process. Specifically, the effects of pH and collector concentration on the flotation performance were investigated. Subsequently, Fourier-transform infrared (FTIR) spectroscopy, Atomic Force Microscopy imaging (AFM) and zeta potential measurements were employed to understand the interfacial reaction between the collector and magnesite, talc and quartz, respectively. The reverse flotation tests results showed that the optimal conditions for separating silicates from magnesite were pH 10 using a collector concentration of 120 g/t. Optimal conditions (pulp pH 10 and 120 g/t alkyl ether amine collector) in a continuous reverse flotation process improved Mg concentrate grade from 22.9 % to 24.5 % while reducing silicon (Si) content from 3.8 wt% to 1.1 wt%. The zeta potential analysis showed that, at pH 10, the collector exhibited stronger adsorption on quartz than on magnesite. Complementary FTIR analysis confirmed adsorption was not restricted to quartz but also affected talc in the feed sample. These results indicate the collector could be effectively utilized in a dual reverse flotation process to reduce Si content by removing both quartz and talc. The findings contribute to advancing metallurgical processing in the concentration of magnesite ore, which could be further processed for Mg production
Silica-based encapsulation for immobilizing heavy metal mobility in agricultural soil
No full textData source: supplementary information, https://doi.org/10.1007/s11270-025-08679-4Stabilization and immobilization techniques have been applied to mitigate the mobility and bioavailability of metal(loid)s in agricultural soils. However, conventional chemical stabilizers alter soil physicochemical properties, potentially impairing plant growth. As an alternative, silica (Si), an abundant component of natural soils, has demonstrated potential in mitigating heavy metal toxicity in plants. This study introduces silica encapsulation of soil particles as an innovative stabilization approach to restrict the translocation of metal(loid)s from soil to crops. The application of silica encapsulation reduced the leachable concentrations of Pb, Zn, and Cu, as determined by the Toxicity Characteristic Leaching Procedure (TCLP), by up to 34.6%, 19.7%, and 11.8%, respectively. Bioaccessible concentrations also decreased by up to 12.0% (Pb), 15.6% (Zn), and 19.4% (Cu). Notably, silica encapsulation effectively reduced heavy metal mobility even under accelerated wet-dry aging conditions. The technique also enhanced the germination rates of Lactuca sativa and Hordeum vulgare by up to 11-fold in heavy metal-contaminated soils and decreased heavy metal accumulation in barley roots by as much as 97.3%. Furthermore, silica encapsulation demonstrated effectiveness across various soil types and contamination levels, underscoring its robustness as a stabilization strategy. These findings not only demonstrate the practical potential of silica encapsulation in mitigating heavy metal transfer but also provide new insights into the stabilization mechanisms involving silica layers on soil particles, thereby contributing to safer and more sustainable agricultural practices
The resilient microbiome: how baseline gut microbial composition influences response to cancer treatment
No full textOnlinePublThe human gut microbiome is increasingly recognized as a key modulator of health and disease, with growing evidence supporting its influence on responses to cancer therapy. An important aspect of this relationship is gut microbial resilience, defined as the ability of the microbiome to recover its ecological equilibrium following disruption. Individual variations in microbial composition significantly influence resilience and, consequently, personalized responses to cancer treatments. However, the underlying functional characteristics of a resilient microbiome remain incompletely understood. Identifying specific microbial profiles with greater resilience to cancer therapies could improve the ability to predict treatment responses and mitigate adverse events. However, despite growing interest, a lack of longitudinal and mechanistic studies currently limits their clinical translation. This review examines current literature on gut microbiome compositions and individual treatment response to cancer therapy, with a focus on microbial features linked to resilience which could enable prediction of adverse response. While the use of microbial metabolites as predictive biomarkers (e.g. short-chain fatty acids and bile acids) is promising, further longitudinal and interventional studies are essential to support clinical application. Establishing specific microbial and metabolite profiles that promote resilience is essential to advance this emerging field of personalized gut-microbiome therapy.Nicole S. L. Chan, Courtney Cross, Clive A. Prestidge, Hannah R. Wardill, Joanne Bowen, Paul Joyc
Practitioner Experiences of Integrative health CarE [PEICE]: A qualitative descriptive study
No full textLink to a related website: https://orcid.org/0000-0001-7785-3261, ORCID profile - Veziari, YasaminBackground: Evidence suggests that some models of care may have a positive impact on health worker wellbeing and retention. This study set out to understand health practitioners’ experiences of working within an integrative health care (IHC) setting in Australia, and the impact of such on practitioners’ clinical behaviour and well-being.
Methods: The study employed a qualitative descriptive design and purposive sampling. Health care practitioners of any discipline working in an IHC setting in Australia in a clinical capacity were invited to participate in an online, semi-structured interview. Interview audio-recordings were transcribed verbatim and analysed using deductive thematic analysis.
Results: Twenty-four health practitioners from twelve distinct professions partook in an interview. Four themes emerged from the data, including (i) Transition to practice (e.g. Changed approach to patient care), (ii) Professional interactions (e.g. changing perceptions of, and relationships with other healthcare providers), (iii) Job satisfaction (e.g. rewards and frustrations of working in an IHC setting), and (iv) Impacts on health and wellbeing (e.g. positive and negative health impacts).
Conclusion: The study uncovered new insights into health practitioners’ experiences of working within an IHC setting; including impacts on clinical knowledge, skills, behaviours and relationships, as well as practitioner health, wellbeing and job satisfaction. Given the potential implications of these findings on health workforce supply, quality of care and patient satisfaction, there is a need to build upon this work to determine whether the implementation of IHC models of care in different settings yields meaningful and sustainable clinical, social and economic benefit
Learning instrumental variable representation for debiasing in recommender systems
No full textRecommender systems are essential for filtering content to match user preferences. However, traditional recommender systems often suffer from biases inherent in the data, such as popularity bias. These biases, particularly those stemming from latent confounders, can result in inaccurate recommendations and reduce both the diversity and effectiveness of the system. Existing debiasing methods for recommender systems, however, either fail to account for latent confounders or rely on predefined instrumental variables (IVs). To address this research gap, we propose a novel causality-based recommendation algorithm, Data-driven IV representation learning for debiasing in Recommender System (DIVRS), which enables the learning of IV representation directly from user-item interaction data. By leveraging the learned IV representation, DIVRS decomposes user behaviour into causal and confounding relationships to address potential bias in recommender systems. Additionally, we introduce Orthogonal Promotion Regularisation (OPR) for DIVRS to address the problem that Graph Convolutional Networks (GCNs) amplify bias. We also propose a variant of GCNs for DIVRS, called DIVRS-GCN. Experimental results on the Douban-Movie and Movielens-10M datasets demonstrate that both DIVRS and DIVRS-GCN effectively mitigate confounding bias while outperform the state-of-the-art methods in recommendation performance. For example, on both datasets, our DIVRS and DIVRS-GCN improve Recall@20 by up to 10.98 %. This validates their effectiveness and robustness. Our approaches improve recommendation accuracy while delivering more balanced and diverse suggestions, effectively addressing the limitations of existing IV-based recommender systems