Determination of levofloxacin by HPLC with fluorescence detection in human breast milk

Aggregation-induced-emission red carbon dots for ratiometric sensing of norfloxacin and anti-counterfeiting

The detection of trace antibiotic residues holds significant importance because it's related to food safety and human health. In this study, we developed a new high-yield red-emitting carbon dots (R-CDs) with aggregation-induced emission properties for ratiometric sensing of norfloxacin. R-CDs were prepared in 30 min using an economical and efficient microwave-assisted method with tartaric acid and o-phenylenediamine as precursors, achieving a high yield of 34.4 %. R-CDs showed concentration-dependent fluorescence and aggregation-induced-emission properties. A ratiometric fluorescent probe for detecting the norfloxacin was developed. In the range of 0-40 μM, the intensity ratio of two emission peaks (I445 nm/I395 nm) towards norfloxacin show good linear relationship with its concentrations and a low detection limit was obtained (36.78 nM). In addition, complex patterns were developed for anti-counterfeiting based on different emission phenomenon at different concentrations. In summary, this study designed a novel ratiometric fluorescent probe for detection of norfloxacin, which greatly shortens the detection time and improves efficiency compared with high-performance liquid chromatography and other methods. The study will promote the application of carbon dots in anti-counterfeiting and other related fields, laying the foundation for the preparation of low-cost photosensitive anti-counterfeiting materials.

In-situ SERS detection of quinolone antibiotic residues in aquaculture water by multifunctional Fe3O4@mTiO2@Ag nanoparticles

Antibiotic residues in aquaculture environments disrupt the ecosystem balance and pose a potential hazard to human health when entering the food chain. Therefore, ultra-sensitive detection of antibiotics is necessary. In this study, a multifunctional Fe3O4@mTiO2@Ag core-shell nanoparticle (NP), synthesized using a layer-by-layer method, was demonstrated to be useful as an enhanced substrate for in-situ surface-enhanced Raman spectroscopy (SERS) detection of various quinolone antibiotics in aqueous environments. The results showed that the minimum detectable concentrations of the six investigated antibiotics were 1 × 10-9 mol/L (ciprofloxacin, danofloxacin, enoxacin, enrofloxacin, and norfloxacin) and 1 × 10-8 mol/L (difloxacin hydrochloride) under the enrichment and enhancement of Fe3O4@mTiO2@Ag NPs. Additionally, there was a good quantitative relationship between the antibiotics concentrations and SERS peak intensities within a certain detection range. The results of the spiked assay of actual aquaculture water samples showed that the recoveries of the six antibiotics ranged from 82.9% to 113.5%, with relative standard deviations ranging from 1.71% to 7.24%. In addition, Fe3O4@mTiO2@Ag NPs achieved satisfactory results in assisting the photocatalytic degradation of antibiotics in aqueous environments. This provides a multifunctional solution for low concentration detection and efficient degradation of antibiotics in aquaculture water.

Magnetic Fe3O4@COF@Ag SERS substrate combined with machine learning algorithms for detection of three quinolone antibiotics: Ciprofloxacin, norfloxacin and levofloxacin

Quinolone antibiotics have good antibacterial properties and are commonly used antibiotics in the dairy industry. Currently, the problem of excessive antibiotics in dairy products is very serious. As an ultra-sensitive detection technology, Surface-Enhanced Raman Scattering (SERS) was applied to the detection of quinolone antibiotics in this work. In order to classify and quantify three antibiotics (Ciprofloxacin, Norfloxacin, Levofloxacin) with highly similar molecular structures, a combination of magnetic COF-based SERS substrate and machine learning algorithms (PCA-k-NN, PCA-SVM, PCA-Decision Tree) was used. The classification accuracy of the spectral dataset could reach 100% and the results of LOD calculation were: CIP: 5.61 × 10^-9M, LEV: 1.44 × 10^-8M, NFX: 1.56 × 10^-8M. This provides a new method for the detection of antibiotics in dairy products.

Amphotericin B- and Levofloxacin-Loaded Chitosan Films for Potential Use in Antimicrobial Wound Dressings: Analytical Method Development and Its Application

Levofloxacin (LVX) and amphotericin B (AMB) have been widely used to treat bacterial and fungal infections in the clinic. Herein, we report, for the first time, chitosan films loaded with AMB and LVX as wound dressings to combat antimicrobial infections. Additionally, we developed and validated a high-performance liquid chromatography (HPLC) method coupled with a UV detector to simultaneously quantify both AMB and LVX. The method is easy, precise, accurate and linear for both drugs at a concentration range of 0.7-5 µg/mL. The validated method was used to analyse the drug release, ex vivo deposition and permeation from the chitosan films. LVX was released completely from the chitosan film after a week, while approximately 60% of the AMB was released. Ex vivo deposition study revealed that, after 24-hour application, 20.96 ± 13.54 µg of LVX and approximately 0.35 ± 0.04 µg of AMB was deposited in porcine skin. Approximately 0.58 ± 0.16 µg of LVX permeated through the skin. AMB was undetectable in the receptor compartment due to its poor solubility and permeability. Furthermore, chitosan films loaded with AMB and LVX were found to be able to inhibit the growth of both Candida albicans and Staphylococcus aureus, indicating their potential for antimicrobial applications.