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<p>In this study, surface-enhanced Raman spectroscopy (SERS) is used to identify the characteristic SERS spectral features of the 30&#xa0;kDa filtrate portions of blood serum samples of thyroid-stimulating hormone (TSH) patients. SERS is an effective technique for the characterization and screening of diseases using body fluids including blood which contains both low molecular weight fraction (LMWF) and high molecular weight fraction (HMWF) proteins. The disease biomarkers of TSH patients are associated with LMWF, which are suppressed due to HMWF of blood serum, making it difficult to analyze the disease-positive samples at the early stage. The objective of this study is to separate the filtrate portions from whole blood serum samples by using 30&#xa0;kDa Amicon ultrafiltration centrifugal devices retaining proteins smaller than 30&#xa0;kDa and removing larger ones. This method facilitates a more effective acquisition of SERS spectral features from smaller proteins that may be associated with thyroid disease. SERS is applied as a diagnostic technique to identify abnormal TSH levels (hypothyroid and hyperthyroid) by comparing the spectral features of healthy and disease samples. Moreover, the chemometric techniques like principal component analysis (PCA) and partial least square regression analysis (PLSR) to check the potential of SERS to diagnose and differentiate blood filtrate samples from healthy samples. PCA successfully differentiates the SERS spectral data sets of both hypothyroid and hyperthyroid from healthy filtrate samples. The PLSR model was applied to quantitatively access the data of the filtrate portions of hypothyroid and hyperthyroid samples. The PLSR model also showed strong validity in predicting the levels of hypothyroid and hyperthyroid for the unknown samples. These results suggested that SERS is found to be an effective technique and can be applied for early disease diagnosis and detection of biochemical changes in abnormal TSH from the 30&#xa0;kDa filtrates of healthy and diseased serum samples.</p>

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Surface-Enhanced Raman Spectral Monitoring of 30 kDa Filtrate Portions of Blood Serum Samples of Thyroid-Stimulating Hormone (TSH) Patients

  • 期刊论文

  • 发表日期：

    2025年5月28日

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  • Seher Nawabzadi,
  • Saima Afzal,
  • Haq Nawaz,
  • Muhammad Irfan Majeed,
  • Najah Alwadie,
  • Usman Ghaffar,
  • Arslan Bashir,
  • Abu Bakar Salfi,
  • Shanza Rauf,
  • Rida Fatima,
  • Shama Sehar,
  • Saira Dastgir,
  • Ghulam Mustafa,
  • Yasir Arbaz,
  • Muhammad Imran

摘要

In this study, surface-enhanced Raman spectroscopy (SERS) is used to identify the characteristic SERS spectral features of the 30 kDa filtrate portions of blood serum samples of thyroid-stimulating hormone (TSH) patients. SERS is an effective technique for the characterization and screening of diseases using body fluids including blood which contains both low molecular weight fraction (LMWF) and high molecular weight fraction (HMWF) proteins. The disease biomarkers of TSH patients are associated with LMWF, which are suppressed due to HMWF of blood serum, making it difficult to analyze the disease-positive samples at the early stage. The objective of this study is to separate the filtrate portions from whole blood serum samples by using 30 kDa Amicon ultrafiltration centrifugal devices retaining proteins smaller than 30 kDa and removing larger ones. This method facilitates a more effective acquisition of SERS spectral features from smaller proteins that may be associated with thyroid disease. SERS is applied as a diagnostic technique to identify abnormal TSH levels (hypothyroid and hyperthyroid) by comparing the spectral features of healthy and disease samples. Moreover, the chemometric techniques like principal component analysis (PCA) and partial least square regression analysis (PLSR) to check the potential of SERS to diagnose and differentiate blood filtrate samples from healthy samples. PCA successfully differentiates the SERS spectral data sets of both hypothyroid and hyperthyroid from healthy filtrate samples. The PLSR model was applied to quantitatively access the data of the filtrate portions of hypothyroid and hyperthyroid samples. The PLSR model also showed strong validity in predicting the levels of hypothyroid and hyperthyroid for the unknown samples. These results suggested that SERS is found to be an effective technique and can be applied for early disease diagnosis and detection of biochemical changes in abnormal TSH from the 30 kDa filtrates of healthy and diseased serum samples.