m+Medelevator.RU
← Поиск публикаций
Analytical chemistry · 2016

Lab-on-a-Chip-Surface Enhanced Raman Scattering Combined with the Standard Addition Method: Toward the Quantification of Nitroxoline in Spiked Human Urine Samples.

Оценочное исследованиеСтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Hidi Izabella J, Jahn Martin, Weber Karina, Bocklitz Thomas, Pletz Mathias W, Cialla-May Dana, Popp Juergen

Аннотация

The emergence of antibacterial resistance and the development of new drugs lead to a continuous change of guidelines for medical treatments. Hence, new analytical tools are required for the detection of drugs in biological fluids. In this study, the first surface enhanced Raman scattering (SERS) detection of nitroxoline (NTX) in purified water and in spiked human urine samples is reported. Insights concerning the nature of the molecule-metal interaction and its influence on the overall SERS signal are provided. Furthermore, three randomly collected urine samples originating from a healthy volunteer were spiked to assess the limit of detection (LOD), the limit of quantification (LOQ), and the linear dynamic range of the lab-on-a-chip SERS (LoC-SERS) method for NTX detection in human urine. The LOD is ∼3 μM (0.57 mg/L), LOQ ∼ 6.5 μM (1.23 mg/L) while the linear range is between 4.28 and 42.8 μM (0.81-8.13 mg/L). This covers the minimum inhibitory concentration (MIC) values of the most commonly encountered uropathogens. Finally, seven clinical samples having an "Нет данных" NTX concentration were simulated. The LoC-SERS technique combined with the standard addition method and statistical data analysis provided a good prediction of the unknown concentrations. Additionally, it is also demonstrated that the predictions carried out by multicurve resolution alternating least-squares (MCR-ALS) algorithm provides reliable results, and it is preferred to a univariate statistical approach.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты