Degradation of tetrachloroethylene by zero valent iron nanoparticles in the presence of a natural groundwater bacterial biofilm in a sandy porous media

Distinct effects of flow intermittency on the benthic microbial diversity and their denitrification on different substrates

Global climate change has significantly increased the duration of droughts in intermittent rivers, impacting benthic microbial-mediated biogeochemical processes. However, the response mechanisms of biofilms on different substrate types to alternating dry and wet conditions and their related ecosystem functions remain poorly understood. This study uses high-throughput sequencing and enzyme assays to investigate the impact of gradient drought stress on microbial diversity and functional changes of biofilm communities inhabiting on gravel, cobblestone, and sediment. Results showed that the duration of drought significantly affects microbial diversity, with algal and bacterial α-diversity declining under extended drought across gravel, cobblestone, and sediment substrates. At the same time, fungal diversity was less affected, likely due to their distinct ecological niches and reproductive strategies. β-diversity analysis revealed significant changes in community heterogeneity, with algae and bacteria showing increased Bray-Curtis dissimilarities, indicating distinct adaptation strategies that may affect ecosystem functioning. Fungal communities, however, were less impacted by drought-induced heterogeneity changes. Network analysis showed that drought altered microbial network connectivity, with algal networks displaying decreased path distances, while bacterial networks remained stable, suggesting greater resilience to drought stress. Functional enzyme assays revealed significantly reduced denitrification rates across all substrates post-drought, with distinct denitrifying enzyme activity responses depending on substrate type. Partial least squares path modeling revealed that algal biodiversity were closely linked to the maintaining of enzyme activities, particularly denitrification rates of biofilms on cobblestone and gravel. These findings indicated the critical role of substrate types in shaping microbial responses to drought stress, with distinct microbial groups and diversity indices playing key roles in maintaining ecosystem functions. This study highlights the importance of understanding the interactions between microbial community dynamics and ecosystem functions under varying environmental stressors in river ecosystems.

Role of Artificial Intelligence in Drug Discovery and Target Identification in Cancer

Drug discovery and development (DDD) is a highly complex process that necessitates precise monitoring and extensive data analysis at each stage. Furthermore, the DDD process is both timeconsuming and costly. To tackle these concerns, artificial intelligence (AI) technology can be used, which facilitates rapid and precise analysis of extensive datasets within a limited timeframe. The pathophysiology of cancer disease is complicated and requires extensive research for novel drug discovery and development. The first stage in the process of drug discovery and development involves identifying targets. Cell structure and molecular functioning are complex due to the vast number of molecules that function constantly, performing various roles. Furthermore, scientists are continually discovering novel cellular mechanisms and molecules, expanding the range of potential targets. Accurately identifying the correct target is a crucial step in the preparation of a treatment strategy. Various forms of AI, such as machine learning, neural-based learning, deep learning, and network-based learning, are currently being utilised in applications, online services, and databases. These technologies facilitate the identification and validation of targets, ultimately contributing to the success of projects. This review focuses on the different types and subcategories of AI databases utilised in the field of drug discovery and target identification for cancer.

Metallic iron (Fe0)-based materials for aqueous phosphate removal: A critical review

The discharge of excessive phosphate from wastewater sources into the aquatic environment has been identified as a major environmental threat responsible for eutrophication. It has become essential to develop efficient but affordable techniques to remove excess phosphate from wastewater before discharging into freshwater bodies. The use of metallic iron (Fe⁰) as a reactive agent for aqueous phosphate removal has received a wide attention. Fe⁰ in-situ generates positively charged iron corrosion products (FeCPs) at pH > 4.5, with high binding affinity for anionic phosphate. This study critically reviews the literature that focuses on the utilization of Fe⁰-based materials for aqueous phosphate removal. The fundamental science of aqueous iron corrosion and historical background of the application of Fe⁰ for phosphate removal are elucidated. The main mechanisms for phosphate removal are identified and extensively discussed based on the chemistry of the Fe⁰/H₂O system. This critical evaluation confirms that the removal process is highly influenced by several operational factors including contact time, Fe⁰ type, influent geochemistry, initial phosphate concentration, mixing conditions, and pH value. The difficulty in comparing independent results owing to diverse experimental conditions is highlighted. Moreover, contemporary research in progress including Fe⁰/oxidant systems, nano-Fe⁰ application, Fe⁰ material selection, desorption studies, and proper design of Fe⁰-based systems for improved phosphate removal have been discussed. Finally, potential strategies to close the loop in Fe⁰-based phosphate remediation systems are discussed. This review presents a science-based guide to optimize the efficient design of Fe⁰-based systems for phosphate removal.

Investigating the Fe0/H2O systems using the methylene blue method: Validity, applications, and future directions

An innovative approach to characterize the reactivity of metallic iron (Fe⁰) for aqueous contaminant removal has been in use for a decade: The methylene blue method (MB method). The approach considers the differential adsorptive affinity of methylene blue (MB) for sand and iron oxides. The MB method characterizes MB discoloration by sand as it is progressively coated by in-situ generated iron corrosion products (FeCPs) to deduce the extent of iron corrosion. The MB method is a semi-quantitative tool that has successfully clarified some contradicting reports on the Fe⁰/H₂O system. Moreover, it has the potential to serve as a powerful tool for routine tests in the Fe⁰ remediation industry, including quality assurance and quality control (QA/QC). However, MB is widely used as a 'molecular probe' to characterize the Fe⁰/H₂O system, for instance for wastewater treatment. Thus, there is scope to avoid confusion created by the multiple uses of MB in Fe⁰/H₂O systems. The present communication aims at filling this gap by presenting the science of the MB method, and its application and limitations. It is concluded that the MB method is very suitable for Fe⁰ material screening and optimization of operational designs. However, the MB method only provides semi-quantitative information, but gives no data on the solid-phase characterization of solid Fe⁰ and its reaction products. In other words, further comprehensive investigations with microscopic and spectroscopic surface and solid-state analyses are needed to complement results from the MB method.