The transport and fate of antibiotics are significantly influenced by co-existing colloidal and nanosized substances, such as clay particles. Montmorillonite, a common clay mineral with a thin nano-sheet-like structure, enhances antibiotic (e.g., ciprofloxacin) mobility due to its strong adsorption properties. Nevertheless, little is known about how ciprofloxacin systematically influences the charging and aggregation properties of montmorillonite. This study examines the effect of ciprofloxacin on the electrophoretic mobility and hydrodynamic diameter of Na-montmorillonite under varying pH levels and NaCl concentrations. Results show ciprofloxacin promotes aggregation and alters the surface net charge of Na-montmorillonite at acidic to neutral pH, where ciprofloxacin is positively charged. At higher pH levels, where ciprofloxacin is negatively charged, no significant effects are observed. The observed aggregation behaviors align with predictions based on the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. Specifically, the slow aggregation regime, the fast aggregation regime, and the critical coagulation concentration are identified. The relationship between critical coagulation ionic strength and electrokinetic surface charge density is well explained by the DLVO theory with the Debye-Hückel approximations. Additionally, non-DLVO interactions are inferred. At low NaCl and ciprofloxacin concentrations, minimal changes in aggregation and surface charge suggest dispersed montmorillonite may facilitate ciprofloxacin transport, raising environmental concerns.
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http://dx.doi.org/10.3390/nano15050389 | DOI Listing |
Drug Saf
March 2025
Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
Introduction: Most epidemiological studies have found antibiotics to be the most common cause of drug-induced liver injury (DILI). It is unclear what the risk of DILI is associated with different antibiotics.
Objective: The aim of the study was to assess the frequency of DILI due to the most commonly used antibiotics among inpatients, in a population-based setting.
Nanomaterials (Basel)
March 2025
Institute of Life and Environmental Sciences, University of Tsukuba, Tsukuba 305-8572, Ibaraki, Japan.
The transport and fate of antibiotics are significantly influenced by co-existing colloidal and nanosized substances, such as clay particles. Montmorillonite, a common clay mineral with a thin nano-sheet-like structure, enhances antibiotic (e.g.
View Article and Find Full Text PDFNanomaterials (Basel)
March 2025
School of Materials Science and Engineering, Jiamusi University, Jiamusi 154000, China.
This study synthesized graphene oxide (GO)/zinc oxide (ZnO)/silver (Ag) composite materials and investigated their photocatalytic degradation performance for ciprofloxacin (CIP) under visible light irradiation. GO/ZnO/Ag composites with different ratios were prepared via an impregnation and chemical reduction method and characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FT-IR), and X-ray photoelectron spectroscopy (XPS). The results demonstrated that under optimal conditions (20 mg/L CIP concentration, 15 mg catalyst dosage, GO/ZnO-3%/Ag-doping ratio, and pH 5), the GO/ZnO/Ag composite exhibited the highest photocatalytic activity, achieving a maximum degradation rate of 82.
View Article and Find Full Text PDFNanomaterials (Basel)
February 2025
Shandong Provincial Key Laboratory of Molecular Engineering, School of Chemistry and Chemical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China.
Defects and heteroatom doping are two refined microstructural factors that significantly affect the performance of photocatalytic materials. Coupling defect and doping engineering is a powerful approach for designing efficient photocatalysts. In this research, we successfully construct dual defect-engineered BiVO nanosheets (BVO-N-OV) by introducing N doping and oxygen vacancies through ammonium oxalate-assisted thermal treatment of BiVO nanosheets.
View Article and Find Full Text PDFHeliyon
February 2025
Department of Emergency Medicine, Mayo Clinic, Rochester, MN, USA.
Background: Urinary tract infections (UTIs) are among the most common bacterial infections diagnosed in the emergency department. Treatment of UTIs is largely empiric because urine culture results are not rapidly available.
Objectives: We examined whether machine learning could predict antibiotic sensitivities of the urine cultures by using only data available during the clinical encounter.
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