Increased antineoplastic drug concentrations in wastewater stem from ineffective treatment plants and increased usage. Although microrobots are promising for pollutant removal, they face hurdles in developing a superstructure with superior adsorption capabilities, biocompatibility, porosity, and pH stability. This study focused on adjusting the PVP concentration from 0.05 to 0.375 mM during synthesis to create a favorable CMOC structure for drug absorption. Lower PVP concentrations (0.05 mM) yielded a three-dimensional nanoflower structure of CaMoO and CuS nanostructures, whereas five-fold concentrations (0.25 mM) produced a porous structure with a dense CuS core encased in a transparent CaMoO shell. The magnetically movable and pH-stable COF@CMOC microrobot, achieved by attaching CMOC to cobalt ferrite (CoF) NPs, captured doxorubicin efficiently, with up to 57 % efficiency at 200 ng/mL concentration for 30 min, facilitated by electrostatic interaction, hydrogen bonding, and pore filling of DOX. The results demonstrated that DOX removal through magnetic motion showed superior performance, with an estimated improvement of 57% compared to stirring conditions (17 %). A prototype PDMS microchannel system was developed to study drug absorption and microrobot recovery. The CaMoO shell of the microrobots exhibited remarkable robustness, ensuring long-lasting functionality in harsh wastewater environments and improving biocompatibility while safeguarding the CuS core from degradation. Therefore, microrobots are a promising eco-friendly solution for drug extraction. These microrobots show promise for the selective removal of doxorubicin from contaminated wastewater.
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http://dx.doi.org/10.1016/j.chemosphere.2024.142590 | DOI Listing |
Cell Mol Biol (Noisy-le-grand)
January 2025
Department of Pharmaceutical Sciences, College of Pharmacy, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.
Antibiotics play a fundamental role in protecting millions of lives from infectious diseases. However, an important drawback of antibiotic treatment is that each advancement was followed by the development of resistance. This is due to the fact that the majority of pathogenic bacteria are capable of becoming resistant to a number of antimicrobial agents.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Medicinal Chemistry, Faculty of Pharmacy, Zagazig University, Zagazig, Egypt.
Remdesivir and moxifloxacin hydrochloride are among the most frequently co-administered drugs used for COVID-19 treatment. The current work aims to evaluate green spectrophotometric methodologies for estimating remdesivir and moxifloxacin hydrochloride in different matrices for the first time. The proposed approaches were absorbance subtraction, extended ratio subtraction and amplitude modulation methods.
View Article and Find Full Text PDFClin Pharmacokinet
January 2025
Clinical Pharmacology and Toxicology Service, Anesthesiology, Pharmacology and Intensive Care Department, Geneva University Hospitals, 4 Rue Gabrielle Perret-Gentil, 1205, Geneva, Switzerland.
Background And Objective: Fexofenadine is commonly used as a probe substrate to assess P-glycoprotein (Pgp) activity. While its use in healthy volunteers is well documented, data in older adult and polymorbid patients are lacking. Age- and disease-related physiological changes are expected to affect the pharmacokinetics of fexofenadine.
View Article and Find Full Text PDFClin Transl Sci
January 2025
Global Biometrics and Data Management, Pfizer Research and Development, New York, New York, USA.
The pharmaceutical industry constantly strives to improve drug development processes to reduce costs, increase efficiencies, and enhance therapeutic outcomes for patients. Model-Informed Drug Development (MIDD) uses mathematical models to simulate intricate processes involved in drug absorption, distribution, metabolism, and excretion, as well as pharmacokinetics and pharmacodynamics. Artificial intelligence (AI), encompassing techniques such as machine learning, deep learning, and Generative AI, offers powerful tools and algorithms to efficiently identify meaningful patterns, correlations, and drug-target interactions from big data, enabling more accurate predictions and novel hypothesis generation.
View Article and Find Full Text PDFNutrients
December 2024
Department of Environmental and Prevention Sciences, University of Ferrara, 44121 Ferrara, Italy.
Background: A neuroinflammatory disease such as Alzheimer's disease, presents a significant challenge in neurotherapeutics, particularly due to the complex etiology and allostatic factors, referred to as CNS stressors, that accelerate the development and progression of the disease. These CNS stressors include cerebral hypo-glucose metabolism, hyperinsulinemia, mitochondrial dysfunction, oxidative stress, impairment of neuronal autophagy, hypoxic insults and neuroinflammation. This study aims to explore the efficacy and safety of DAG-MAG-ΒHB, a novel ketone diester, in mitigating these risk factors by sustaining therapeutic ketosis, independent of conventional metabolic pathways.
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