Chemometrics-aided surface-enhanced Raman spectrometric detection and quantification of GH and TE hormones in blood.
Creators
- 1. Laser Physics and Spectroscopy Research Group, Department of Physics, University of Nairobi, Nairobi, Kenya.
- 2. Department of Medical Physiology, University of Nairobi, Nairobi, Kenya.
- 3. UNESCO-UNISA Africa Chair in Nanoscience/Nanotechnology, College of Graduate Studies, University of South Africa (UNISA), Pretoria, South Africa.
- 4. School of Health Sciences, Dedan Kimathi University of Technology, Dedan Kimathi, Kenya.
Description
Growth hormone (GH) and testosterone (TE) levels in blood are crucial indicators of human health and performance in clean sports. Deviations from normal levels can signal serious health issues, such as fertility problems, cancer, or pituitary tumors. Existing detection methods for these hormones are often costly, time-consuming, and lack portability. In this study, we explored the potential of Surface-Enhanced Raman Spectroscopy (SERS) in distinguishing blood samples from Sprague Dawley (SD) rats injected with exogenous GH, TE and both hormones from those not injected. Then, used artificial neural network (ANN) models trained, and validated in predicting levels of these hormones in blood. Blood samples from SD rats injected with GH, TE, both hormones, and non-injected rats were analyzed using the SERS method upon 785 nm laser excitation. The recorded Raman spectra from blood of GH and TE injected and non-injected rats displayed hormone-specific band intensity variations. Additionally, Principal Component Analysis (PCA) showed temporal changes in band intensities post-injection, suggesting hormone-induced biochemical alterations. In particular, Raman bands centered around 1378 cm⁻¹ for all groups, 658 cm⁻¹ for GH, and 798 cm⁻¹ for GH and TE displayed significant intensity variations. The ANN models, trained using PCA scores from blood samples with varied hormone concentrations, achieved high predictive accuracy with coefficients of determination (R² > 87.71%) and low root mean square error (RMSE < 0.6436). Elevated hormone levels were initially observed in injected rats, gradually declining over time, with results aligning closely to those obtained via ELISA kits. This work showed that the SERS method can provide rapid (~2 minutes), hormone-independent detection with minimal sample preparation. This approach demonstrated the SERS method's potential for rapid, reliable hormone detection and with customized calibration may be applied in sports doping control, clinical diagnostics, and broader biomedical research.
Open Access
Licence Attribution (CC BY)
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Publication Details
Journal article
Journal:
PloS one
Publisher:
Public Library of Science (PLoS)
ISSN:
19326203
Volume:
20
Pages:
e0323697-e0323697
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Funding
Financial Support
Swedish International Development Cooperation Agency (SIDA) through the International Science Programme (ISP), Uppsala University — Grant: KEN:04
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References
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Y Liu . Detection and identification of estrogen based on surface-enhanced reson...
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Z Birech . Application of Raman spectroscopy in type 2 diabetes screening in blo...
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X Zhou . Bacteria Detection: From Powerful SERS to Its Advanced Compatible Techn...
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MeSH Terms
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Chemical Substances
2 chemical substances identified from Medical Subject Headings (MeSH).