Archives

  • 2018-07
  • 2018-10
  • 2018-11
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • 2020-03
  • 2020-04
  • 2020-05
  • 2020-06
  • 2020-07
  • 2020-08
  • 2020-09
  • 2020-10
  • 2020-11
  • 2020-12
  • 2021-01
  • 2021-02
  • 2021-03
  • 2021-04
  • 2021-05
  • 2021-06
  • 2021-07
  • 2021-08
  • 2021-09
  • 2021-10
  • 2021-11
  • 2021-12
  • 2022-01
  • 2022-02
  • 2022-03
  • 2022-04
  • 2022-05
  • 2022-06
  • 2022-07
  • 2022-08
  • 2022-09
  • 2022-10
  • 2022-11
  • 2022-12
  • 2023-01
  • 2023-02
  • 2023-03
  • 2023-04
  • 2023-05
  • 2023-07
  • 2023-08
  • 2023-09
  • 2023-10
  • 2023-11
  • 2023-12
  • 2024-01
  • 2024-02
  • 2024-03
  • 2024-04

    • In this paper we demonstrate a

    2022-01-26

    In this paper, we demonstrate a Ac-IETD-pNA based TLC-SERS sensing technique combined with machine learning analysis to quantitatively detect seafood allergen in real spoiled tuna samples. We fabricate a diatomaceous earth TLC plate as a separable SERS-active substrate to detect histamine in artificially spoiled tuna solution down to 10 ppm by a BW&TEK portable Raman spectrometer. Support vector machine is a multivariate calibration method based on statistical learning theory and is very powerful in spectroscopy analysis applications owing to its nonlinear characteristics (Dong, Weng, Yang, & Liu, 2015; Wu et al., 2015). Recently, Hu, X. et al. reported a TLC-SERS technique to screen pericarpium papaveris in hot pot condiments using Support vector machine qualification analysis based on first derivative spectra, claiming 100% screening accuracy (Hu, Fang, Han, Liu, & Wang, 2017). However, no quantitative results were obtained and no discussion of detection limit was included in this report. Herein, we applied principal component analysis (PCA) and support vector regression (SVR) to quantitatively analyze the TLC-SERS spectral data of real tuna samples that spoiled at room temperature for 0, 4, 8, 12, 24, 36 and 48 h. PCA was used to extract key features as the input for the SVR model. Compared to traditional linear PLSR model, the PCA-SVR method achieved more accurate quantitative prediction. To the best of knowledge, this is the first attempt to combine TLC-SERS sensing technology with nonlinear regression machine learning method of SVR for quantitative analysis. Our experimental results proved that an SVR-enabled TLC-SERS device, which can be measured by a portable Raman spectrometer, would enable a rapid, cost-effective, reliable, and quantitative on-site sensing method to detect trace level of seafood allergen, and potentially many other targets in complex real biological samples.
    Materials and methods
    Results and discussion
    Conclusions
    Acknowledgements The authors would like to acknowledge the support from the National Institutes of Health under Grant No. 1R21DA0437131, the Unites States Department of Agriculture under Grant No. 2017- 67021-26606 and the National Science Foundation under Grant No. 1701329. A. Tan and Y. Zhao would also like to acknowledge the support from China Scholarship Council.
    Histamine (, ), one of the neurotransmitters, functions through four different histamine receptor subtypes in the whole body. These receptor subtypes, which belong to seven-transmembrane G protein-coupled receptors (GPCRs), are classified into H, H, H, and H receptors. Among them, the H receptor (HR) cloned in early the 2000s is mainly expressed in various immune system cells such as eosinophils, dendritic cells, mast cells, and leukocytes. The HR is also involved in cutaneous tissues and central nervous system. Since indole- or benzimidazole-piperazine derivatives, JNJ7777120 () and JNJ10191584 () shown in , were identified as the first non-imidazole HR selective antagonists through high-throughput screening, various physiological functions of the HR have been elucidated, and the HR has been expected as a therapeutic target for autoimmune and inflammatory diseases. In fact, for example, an HR selective antagonist, JNJ38518168 (), advanced to Phase II in the clinical trial as a remedy for asthma and rheumatoid arthritis. Additionally, HR antagonists have shown synergistic effects with H receptor (HR) antagonists in the treatment of allergic diseases including atopic dermatitis. Thus, HR selective antagonists can be high potential therapeutic candidates, although there are no ligands as approved medicines yet. In design of bioactive molecules, three-dimensional structure information of the target protein is significantly beneficial. However, the X-ray crystal structure analysis of the HR has not succeeded. Although there are various reports of homology modeling of the HR based on the crystal structure of the bovine rhodopsin, the adrenergic GPCR, or the HR, the estimated binding modes of histamine and HR ligands are somewhat different depending on the models. Therefore, the precise binding modes are still unclear.