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<p>Surface-enhanced Raman spectroscopy (SERS) has been shown as effective analytical technique for the detection of dengue fever to overcome its rising mortalities worldwide. The high molecular weight fractions (HMWF) suppress the low molecular weight fractions (LMWF) in blood serum samples which are considered disease biomolecules. The purpose of the study is to target specific disease biomarkers associated with dengue disease which are below 30&#xa0;kDa in size as characteristic SERS spectral peaks. The chemometric methods such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) are also used to classify the SERS spectral datasets of dengue-positive patients and healthy ones. The PCA effectively differentiates the two datasets of 30-kDa filtrate portions of dengue and healthy serum samples. Furthermore, the results of the PLS-DA model show a sensitivity of 85%, a specificity of 98%, and an area under the curve (AUC) value of 0.80 which indicates the validity and authenticity of the constructed PLS-DA model.</p>

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SERS-Based Profiling of Blood Serum Filtrate from Dengue Patients by Using 30-kDa Ultra-Centrifugal Devices

  • 期刊论文

  • 发表日期：

    2025年8月2日

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  • Shanza Rauf,
  • Aneela Falak Sher,
  • Haq Nawaz,
  • Muhammad Irfan Majeed,
  • Najah Alwadie,
  • Hira Shafique,
  • Shama Sehar,
  • Maria Ghafoor,
  • Muhammad Usman,
  • Iqra Mobeen,
  • Rida Fatima,
  • Saima Afzal,
  • Aqsa Luqman,
  • Saira Dastgir,
  • Shama Yaseen,
  • Muhammad Imran

摘要

Surface-enhanced Raman spectroscopy (SERS) has been shown as effective analytical technique for the detection of dengue fever to overcome its rising mortalities worldwide. The high molecular weight fractions (HMWF) suppress the low molecular weight fractions (LMWF) in blood serum samples which are considered disease biomolecules. The purpose of the study is to target specific disease biomarkers associated with dengue disease which are below 30 kDa in size as characteristic SERS spectral peaks. The chemometric methods such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) are also used to classify the SERS spectral datasets of dengue-positive patients and healthy ones. The PCA effectively differentiates the two datasets of 30-kDa filtrate portions of dengue and healthy serum samples. Furthermore, the results of the PLS-DA model show a sensitivity of 85%, a specificity of 98%, and an area under the curve (AUC) value of 0.80 which indicates the validity and authenticity of the constructed PLS-DA model.