BURA Collection: The Experimental Techniques Centre is home to a range of large and small scale characterisation facilities that are managed by a team of dedicated scientific officers.

Phytomining potential of naturally colonising vegetation on coal colliery spoil heaps in South Yorkshire, United Kingdom and Upper Silesia, Poland

2026-10-28T00:00:00Z

Title: Phytomining potential of naturally colonising vegetation on coal colliery spoil heaps in South Yorkshire, United Kingdom and Upper Silesia, Poland Authors: Doyle, Darragh; Szojda, Leszek; Onwukwe, Uche; Anguilano, Lorna Abstract: The environmental legacy of coal mining is characterised by the widespread accumulation of spoil heaps enriched with elements, representing both a persistent ecological liability and an underutilised secondary resource. Phytomining has emerged as a promising sustainable strategy for the recovery of valuable metals from such substrates while simultaneously facilitating environmental remediation. This study evaluates the phytomining potential of two legacy coal colliery spoil heaps located at Barnsley Main (South Yorkshire, United Kingdom) and Kopalnia Węgla Kamiennego (KWK) Dębieńsko (Upper Silesia, Poland). Specific and naturally colonising species were sampled and analysed using X-ray fluorescence (XRF) spectrometry to quantify elemental accumulation within stem and leaf tissues. The results reveal pronounced inter site variability in both species composition and metal uptake capacity. Barnsley Main exhibited elevated concentrations of economically significant metals, particularly Zinc (Zn) and Copper (Cu), with Jacobaea vulgaris and Leucanthemum vulgare demonstrating notable accumulation potential. In contrast, KWK Dębieńsko displayed greater colonial floristic diversity with more spatially distributed, moderate accumulation across multiple taxa. Climatic variability between sites further influences metal mobility and bioavailability, thereby affecting uptake dynamics. Collectively, these findings underscore the viability of coal colliery spoil heaps as substrates for phytomining, while highlighting the importance of site specific environmental and biological factors in determining operational feasibility. The study contributes to the advancements of phytomining as an integrated approach to resource recovery and ecological restoration in post-industrial landscapes. Description: Plant source: Plant material used in this study comprised of naturally colonising vegetation collected from two historic coal colliery spoil heaps: Barnsley Main Colliery, South Yorkshire, United Kingdom (53.55315386642625, -1.45142914692534), and Kopalnia Węgla Kamiennego (KWK) Dębieńsko, Upper Silesia, Poland (50.158144, 18.677301). Plant guidelines: Plant collection was undertaken solely for scientific research purposes from post-industrial sites in accordance with applicable institutional, local and national regulations governing field sampling. Sampling was restricted to naturally established vegetation, and reasonable care was taken to minimise disturbance to the surrounding environment. Plant identifier: Plant species used in this study were identified and verified by Darragh Doyle (Brunel University of London), using standard taxonomic keys and morphological characteristics appropriate for the flora of the United Kingdom and Poland. Species identification was undertaken prior to sample collection and processing to ensure the accurate taxonomic classification of all naturally colonising vegetation included in the study. Herbarium name: Representative voucher specimens of all wild plant species collected during this study have been deposited in the Experimental Techniques Centre (ETC) to ensure the long-term preservation and accessibility of the plant material. Specimen voucher ID: The corresponding voucher specimen accession numbers are as follows: Collection-Voucher ID: PHY-UK-POL-001. Permissions to collect the plants/Plant Parts: Not applicable.

Harnessing the Sustainable Approach for Copper Nanoparticle Biosynthesis: Investigation of Antiviral and Antioxidant Efficacy and an In Silico Study

2026-10-01T00:00:00Z

Title: Harnessing the Sustainable Approach for Copper Nanoparticle Biosynthesis: Investigation of Antiviral and Antioxidant Efficacy and an In Silico Study Authors: AL-Timimi, Iman AJ; Al Yasiri, Mohammed J; Murad, Diya MA; Jassim, Amar Yasser; Jassim, Nawras T; Onwukwe, Uche K Abstract: The emergence of SARS-CoV-2 and other virus threats has renewed interest in nanoparticles as potential antivirals. Green synthesis of nanoparticles using biological methods offers an eco-friendly, cost-effective alternative to conventional approaches. In this study, copper nanoparticles (Cu-NPs) were biosynthesized using Artemisia sieberi (A.s) florets extract, which acts as a reducing, capping, and stabilizing agent. The synthesized Cu-NPs/A.s were characterized using transmission electron microscopy (TEM), UV-Visible spectroscopy, energy-dispersive X-ray spectroscopy (EDX), and dynamic light scattering (DLS). The antiviral and antioxidant activities of Cu-NPs/A.s were evaluated, and molecular docking was performed to explore possible interactions between Cu-NPs/A.s with SARS-CoV-2 main protease and influenza A virus RNA polymerase as a hypothesis-generating approach. Structural and morphological characterisations confirmed successful nanoparticle formation, and Cu nanoparticles exhibited smaller particle dimensions (particle size of 63.7 ± 19.5). The Cu-NPs/A.s demonstrated notable antioxidant activity (55% scavenging in phosphomolybdate assay) compared to ascorbic acid and a strong inhibitory effect against influenza A virus (IAV) (70.67%). Docking studies indicated favorable binding energy interactions between chlorogenic acid - copper nanoparticles (CGA-Cu NPs /A.s) and SARS-CoV-2 are -8.22 kcal/mol; similarly, the influenza A virus (IAV) gives the binding energy -9.22 kcal/mol, which may inform future experimental investigations. The DFT parameters indicate that the Cu-complex possesses favourable electronic properties, a substantial charge transfer capability, and elevated reactivity. To assess organ-specific toxicity, bioavailability and metabolic interactions, a full computational toxicological evaluation using ProTox-3.0 is performed based on a chemical model for a combination hearing aid.

Seaweed in the UK food system: pitfalls and pathways to scaling up sustainably

2022-09-01T00:00:00Z

Title: Seaweed in the UK food system: pitfalls and pathways to scaling up sustainably Authors: Fallon, N; Schmidt Rivera, X; Anguilano, L; Paterson, S Editors: Bruce, D; Bruce, A Abstract: Within an increased global focus on the Blue Economy, seaweed has the potential to play a much larger role in the future of the UK food systems contributing to multiple environmental, economic, social and health benefits. Seaweed is currently used along the UK food chain as fertiliser, animal feed, in food processing, and as a low-carbon, nutrient dense food source. Mapping conducted using publicly available online sources identified 60 seaweed producers operating in the UK in 2021. These are predominantly small-scale harvesters and producers operating under a range of business models. However, with new enterprises entering the market involving larger scale industrial production and mechanised harvesting methods, the UK seaweed industry appears to be at the precipice of major changes. Scaling up the industry is seen as a priority for UK and devolved governments and an attractive sustainable investment option for venture capital. However, the potential impacts on the marine ecosystem and coastal livelihoods from an expected rapid expansion are currently unknown. In addition, regulation of the industry and the complex land and sea policy landscape is yet to be fully explored within the context of an expanded seaweed industry. Efforts have been expressed by government and industry bodies to ensure industry growth protects coastal communities and does not come at an environmental cost, but questions remain with regards to rapidly shifting power dynamics and industry pressures to deliver returns on investment in a global market. This paper will draw on examples from historical attempts to scale up seaweed production as well as other food-related industries to identify potential pitfalls for the industry to avoid if it is to find a path towards sustainable and responsible growth. More attention needs to be paid to the political economy of the seaweed industry, in particular the influence of powerful market actors and how this may impact the trajectory of the industry.

Machine learning approaches for data-driven hydrocarbon bioaugmentation and phytoremediation: the role of multi-omics insights

2026-03-05T00:00:00Z

Title: Machine learning approaches for data-driven hydrocarbon bioaugmentation and phytoremediation: the role of multi-omics insights Authors: Okafor, UC; Alghamdi, SM; Anguilano, L; Yang, Y Abstract: Hydrocarbon contamination, particularly with polycyclic aromatic hydrocarbons (PAHs), poses a significant environmental challenge due to its persistence and carcinogenic effects on ecosystems and human health globally. This review explores how ML algorithms can enhance the efficiency of bio-augmentation and phytoremediation through predictive modeling, real-time optimization of microbial consortia, and plant species selection. Traditional bioremediation methods, such as bioaugmentation and phytoremediation, are characterized by slow degradation rates and sub-optimal performance in complex, multi-contaminant environmental milieus. The use of machine learning (ML) models with multi-omics data presents an advanced predictive approach to optimizing bioremediation processes by providing a systematic understanding of microbial and plant-mediated hydrocarbon degradation strategies and processes. ML models can predict which microbial strains or plant species will effectively degrade hydrocarbons under specific environmental conditions by utilizing supervised learning methods such as support vector machines and neural networks. Additionally, the combination of multi-omics data with ML facilitates the identification of critical genes, enzymes, and metabolic pathways involved in the degradation of hydrocarbons, and offers insights into the molecular mechanisms which drive the bioremediation process. The translation of laboratory-based ML models into large-scale, real-world bioremediation strategy is hindered by the complex, dynamic nature of our contaminated environments. This review paper showcases these hinderances and provides a direction for future research, including the development of field-deployable technologies, adaptive ML models, and real-time environmental monitoring strategies. The integration of ML with multi-omics holds substantial promise for enhanced efficiency, adaptability, and scalability of bioremediation strategies which ultimately mitigates carcinogenic risks often associated with hydrocarbon-polluted lithosphere.