In the recent years, endocrine disrupting compounds (EDCs) has received increasing attention due to their significant toxic effects on human beings and wildlife by affecting their endocrine systems. As an important group of emerging pollutant, EDCs have been detected in various aquatic environments, including surface waters, groundwater, wastewater, runoff, and landfill leachates. Their removal from water resources has also been an emerging concern considering growing population as well as reducing access to fresh water resources. EDC removal from wastewaters is highly dependent on physicochemical properties of the given EDCs present in each wastewater types as well as various aquatic environments. Due to chemical, physical and physicochemical diversities in these parameters, variety of technologies consisting of physical, biological, electrochemical, and chemical processes have been developed for their removal. This review highlights that the effectiveness of EDC removal is highly dependent of selecting the appropriate technology; which decision is made upon a full wastewater chemical characterization. This review aims to provide a comprehensive perspective about all the current technologies used for EDCs removal from various aquatic matrices along with rising challenges such as the antimicrobial resistance gene transfer during EDC treatment.
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http://dx.doi.org/10.1016/j.envres.2021.112196 | DOI Listing |
J Hematol Oncol
January 2025
Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117600, Singapore.
The tumor microenvironment (TME) is integral to cancer progression, impacting metastasis and treatment response. It consists of diverse cell types, extracellular matrix components, and signaling molecules that interact to promote tumor growth and therapeutic resistance. Elucidating the intricate interactions between cancer cells and the TME is crucial in understanding cancer progression and therapeutic challenges.
View Article and Find Full Text PDFDiagn Progn Res
January 2025
Department of Applied Health Sciences, College of Medicine and Health, University of Birmingham, Edgbaston, Birmingham, UK.
Background: Pressure injuries (PIs) place a substantial burden on healthcare systems worldwide. Risk stratification of those who are at risk of developing PIs allows preventive interventions to be focused on patients who are at the highest risk. The considerable number of risk assessment scales and prediction models available underscores the need for a thorough evaluation of their development, validation, and clinical utility.
View Article and Find Full Text PDFAlzheimers Res Ther
January 2025
Radiology Department, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Background: The imbalance of glutamate (Glu) and gamma-aminobutyric acid (GABA) neurotransmitter system plays a crucial role in the pathogenesis of Alzheimer's disease (AD). Riluzole is a Glu modulator originally approved for amyotrophic lateral sclerosis that has shown potential neuroprotective effects in various neurodegenerative disorders. However, whether riluzole can improve Glu and GABA homeostasis in AD brain and its related mechanism of action remain unknown.
View Article and Find Full Text PDFEnviron Microbiome
January 2025
Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA.
Background: Viruses that infect prokaryotes (phages) constitute the most abundant group of biological agents, playing pivotal roles in microbial systems. They are known to impact microbial community dynamics, microbial ecology, and evolution. Efforts to document the diversity, host range, infection dynamics, and effects of bacteriophage infection on host cell metabolism are extremely underexplored.
View Article and Find Full Text PDFJ Cheminform
January 2025
Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, UK.
Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that 'stitches' the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein-ligand complex conformation than general methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode.
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