Applied Physics A

, 123:141 | Cite as

Exploiting LBL-assembled Au nanoparticles to enhance Raman signals for point-of-care testing of osteoporosis with excreta sample

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Abstract

Due to the intrinsic lack of specific biomarkers, there is an increasing demand for degenerative diseases to develop a testing method independent upon the targeting biomolecules. In this paper, we proposed a novel idea for this issue which was to analyze the characteristic information of metabolites with Raman spectrum. First, we achieved the fabrication of stable, uniform and reproducible substrate to enhance the Raman signals, which is crucial to the following analysis of information. This idea was confirmed with the osteoporosis-modeled mice. Furthermore, the testing results with clinical samples also preliminarily exhibited the feasibility of this strategy. The substrate to enhance Raman signal was fabricated by the layer-by-layer assembly of Au nanoparticles. The osteoporosis modeling was made by bilateral ovariectomy. Ten female mice were randomly divided into two groups. The urine and dejecta samples of mice were collected every week. Clinic urine samples were collected from patients with osteoporosis while the controlled samples were from the young students in our university. The LBL-assembled substrate of Au nanoparticles was uniform, stable and reproducible to significantly enhance the Raman signals from tiny amount of samples. With a simple data processing technique, the Raman signal-based method can effectively reflect the development of osteoporosis by comparison with micro-CT characterization. Moreover, the Raman signal from samples of clinic patients also showed the obvious difference with that of the control. Raman spectrum may be a good tool to convey the pathological information of metabolites in molecular level. Our results manifested that the information-based testing is possibly feasible and promising. Our strategy utilizes the characteristic information rather than the biological recognition to test the diseases which are difficult to find specific biomarkers. This will be greatly beneficial to the prevention and diagnosis of degenerative diseases. Also, we believe the combination of big bio-data and characteristic recognition will change the current paradigm of medical diagnosis essentially.

Keywords

Osteoporosis Gold Nanoparticles Surface Enhance Raman Scattering Raman Signal Nanoparticulate Film 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgements

This work was supported by the National Basic Research Program of China under Grant 2013CB733801 and the National Science Foundation of China under Grant 21,273,002. Jian F. Sun is also thankful to the supports from the ‘QingLan’ project of Jiangsu province and the special fund for the top doctoral thesis of Chinese Education Ministry (201,174). Jian F. Sun and Ning Gu are thankful to the supports from Collaborative Innovation Center of Suzhou Nano Science and Technology.

Supplementary material

339_2017_774_MOESM1_ESM.docx (269 kb)
Supplementary material 1 (DOCX 269 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Jiangsu Key Laboratory of Biomaterials and Devices, School of Biological Science and Medical EngineeringSoutheast UniversityNanjingChina
  2. 2.School of MedicineSoutheast UniversityNanjingChina
  3. 3.Second Affiliated Hospital of Nanjing Medical UniversityNanjingChina
  4. 4.State Key Laboratory of Bioelectronics, School of Biological Science and Medical EngineeringSoutheast UniversityNanjingChina
  5. 5.Zhongda HospitalNanjingChina

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