Literature DB >> 27570877

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

Izabella J Hidi1,2, Martin Jahn1,2, Karina Weber1,2,3, Thomas Bocklitz1, Mathias W Pletz4,3, Dana Cialla-May1,2,3, Juergen Popp1,2,3.   

Abstract

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 "unknown" 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.

Entities:  

Mesh:

Substances:

Year:  2016        PMID: 27570877     DOI: 10.1021/acs.analchem.6b02316

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  5 in total

1.  Imaging of PD-L1 in single cancer cells by SERS-based hyperspectral analysis.

Authors:  Wei Zhang; Jake S Rhodes; Kevin R Moon; Beatrice S Knudsen; Linda Nokolova; Anhong Zhou
Journal:  Biomed Opt Express       Date:  2020-10-08       Impact factor: 3.732

2.  Present and Future of Surface-Enhanced Raman Scattering.

Authors:  Judith Langer; Dorleta Jimenez de Aberasturi; Javier Aizpurua; Ramon A Alvarez-Puebla; Baptiste Auguié; Jeremy J Baumberg; Guillermo C Bazan; Steven E J Bell; Anja Boisen; Alexandre G Brolo; Jaebum Choo; Dana Cialla-May; Volker Deckert; Laura Fabris; Karen Faulds; F Javier García de Abajo; Royston Goodacre; Duncan Graham; Amanda J Haes; Christy L Haynes; Christian Huck; Tamitake Itoh; Mikael Käll; Janina Kneipp; Nicholas A Kotov; Hua Kuang; Eric C Le Ru; Hiang Kwee Lee; Jian-Feng Li; Xing Yi Ling; Stefan A Maier; Thomas Mayerhöfer; Martin Moskovits; Kei Murakoshi; Jwa-Min Nam; Shuming Nie; Yukihiro Ozaki; Isabel Pastoriza-Santos; Jorge Perez-Juste; Juergen Popp; Annemarie Pucci; Stephanie Reich; Bin Ren; George C Schatz; Timur Shegai; Sebastian Schlücker; Li-Lin Tay; K George Thomas; Zhong-Qun Tian; Richard P Van Duyne; Tuan Vo-Dinh; Yue Wang; Katherine A Willets; Chuanlai Xu; Hongxing Xu; Yikai Xu; Yuko S Yamamoto; Bing Zhao; Luis M Liz-Marzán
Journal:  ACS Nano       Date:  2019-10-08       Impact factor: 15.881

3.  Machine Learning-Assisted Sampling of Surfance-Enhanced Raman Scattering (SERS) Substrates Improve Data Collection Efficiency.

Authors:  Tatu Rojalin; Dexter Antonio; Ambarish Kulkarni; Randy P Carney
Journal:  Appl Spectrosc       Date:  2021-08-03       Impact factor: 2.388

4.  Surface enhanced Raman scattering artificial nose for high dimensionality fingerprinting.

Authors:  Nayoung Kim; Michael R Thomas; Mads S Bergholt; Isaac J Pence; Hyejeong Seong; Patrick Charchar; Nevena Todorova; Anika Nagelkerke; Alexis Belessiotis-Richards; David J Payne; Amy Gelmi; Irene Yarovsky; Molly M Stevens
Journal:  Nat Commun       Date:  2020-01-10       Impact factor: 14.919

Review 5.  Review of Integrated Optical Biosensors for Point-Of-Care Applications.

Authors:  Yung-Tsan Chen; Ya-Chu Lee; Yao-Hsuan Lai; Jin-Chun Lim; Nien-Tsu Huang; Chih-Ting Lin; Jian-Jang Huang
Journal:  Biosensors (Basel)       Date:  2020-12-18
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.