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This study aims to develop a rapid bacterial antibiotic susceptibility test (AST) method by Bacteria-aptamer@AgNPs-surface enhanced Raman spectroscopy (SERS) and further evaluate the influence of different antibiotics on the Raman intensity of bacteria. The Raman intensity of Escherichia coli O157:H7 (E. coli O157:H7) and Staphylococcus aureus (S. aureus) in the presence of different concentrations of antibiotics in 2 h was detected by Bacteria-aptamer@AgNPs-SERS in this study. Our results found that the bacteria Raman signal peak at 735 cm and the minimum inhibitory concentration (MIC) value was determined in 1 h according to Raman signals. In 2 h, the bacteria Raman signal growth at sub-MIC concentrations of four different kinds of antibiotics and the bacteria colony-forming unit (CFU) have similar enhancements. SERS utilizes special functions of rough metal surfaces and offers a huge enhancement of Raman intensities with reduced fluorescence backgrounds, which makes it an ultrasensitive tool of detection. This rapid AST method and the enhancement effect should be of value in search of new antibiotic drugs.
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http://dx.doi.org/10.1007/s42770-020-00282-5 | DOI Listing |
Front Bioeng Biotechnol
August 2025
Department of Orthopaedics and Traumatology, Medical University of Innsbruck, Innsbruck, Austria.
Bone infections caused by and are serious complications in orthopedic surgery. These infections commonly occur in joint replacements, fracture management, and bone grafting procedures. Rapid and accurate pathogen-specific diagnostic methods are urgently needed to support early clinical decisions.
View Article and Find Full Text PDFACS Appl Mater Interfaces
September 2025
Key Laboratory of Functional Inorganic Material Chemistry, Ministry of Education of the People's Republic of China, National Center for International Research on Catalytic Technology, School of Chemistry and Materials Science, Heilongjiang University, Harbin 150080, P. R. China.
Seawater electrolysis offers a sustainable pathway for green hydrogen production, but chloride-induced side reactions, particularly chlorine evolution (ClER), limit the stability and efficiency of catalysts. Based on an interface-engineering strategy, a bifunctional CoP-MXene electrocatalyst was designed and fabricated, in which electrons are transferred from the Ti sites of the MXene support to the adjacent Co active centers of CoP. This directional electron donation modulates the Co electronic structure, generating electron-rich Co sites that effectively suppress Cl adsorption via electronic repulsion while preserving the OH reaction pathways through favorable proton-electron coupling.
View Article and Find Full Text PDFCNS Neurosci Ther
September 2025
Department of Pharmacy, Faculty of Health and Life Sciences, Daffodil International University, Dhaka, Bangladesh.
Introduction: The microbiota-gut-brain axis (MGBA), a complex two-way connection between the gut microbiota and the brain, has become a key regulator of neurological and neuropsychiatric disorders. Neurological disorders and gut microbiota dysbiosis are linked to these diseases. Changes in gut microbiota can lead to neurotransmitter imbalances, oxidative stress, and neuroinflammation.
View Article and Find Full Text PDFJ Inorg Biochem
August 2025
Faculty of Chemistry, University of Wroclaw, F. Joliot - Curie 14, 50-383 Wroclaw, Poland.
This study presents the synthesis, structural characterization, and biological evaluation of three nickel(II) complexes containing bioactive ligands: two bidentate pyridyl alcohols (2-pymetH and 2-pyetH) and a mixed-ligand system with memantine and acetylacetone. Single-crystal X-ray diffraction revealed that all complexes adopt a distorted octahedral geometry with a {NiN₂O₄} coordination core, differing in ligand orientation, symmetry, and supramolecular packing. Complementary spectroscopic techniques, including FT-IR, Raman, and UV-Vis, confirmed successful ligand coordination and complex integrity.
View Article and Find Full Text PDFAnal Chim Acta
October 2025
State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing, 100084, China. Electronic address:
Raman spectroscopy has attracted significant attention in various biochemical detection fields, especially in the rapid identification of pathogenic bacteria. The integration of this technology with deep learning to facilitate automated bacterial Raman spectroscopy diagnosis has emerged as a key focus in recent research. However, the diagnostic performance of existing deep learning methods largely depends on a sufficient dataset, and in scenarios where there is a limited availability of Raman spectroscopy data, it is inadequate to fully optimize the numerous parameters of deep neural networks.
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