Surface-enhanced Raman spectroscopy for the characterization of filtrate portions of hepatitis B blood serum samples using 100 kDa ultra filtration devices.

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Tác giả: Norah A Albekairi, Abdulrahman Alshammari, Imran Amin, Eman Fatima, Munazza Hakeem, Munawar Hussain, Mahrosh Javed, Muhammad Irfan Majeed, Sana Mehmood, Haq Nawaz, Nosheen Rashid, Abu Bakar Salfi, Muhammad Hafeez Ullah, Arslan Yousaf

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: England : Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 222924

The blood serum of patients infected by the Hepatitis B virus contains high molecular weight fractions and low molecular weight fractions (LMWF) of biomarker proteins of the disease. The LMWF including the associated peptidome and metabolome, is recognized as a critical molecular population with high potential for research on disease-associated biomarkers. This fraction of biomarkers can be suppressed by HMWF, proteins such as albumin, and immunoglobulins hence difficult to be detected. The purpose of this study is to separate HMWF) and LMWF using 100 kDa centrifugal filtration devices resulting in two parts including residue (HMWF) and filtrate parts (LMWF) of blood serum followed by the analysis of the later part employing surface-enhanced Raman spectroscopy (SERS). This strategy can enhance this optical technique's capability to characterize the biochemical changes caused by the infection of HBV and the diagnosis of the disease. The silver nanoparticles (Ag-NPs) were employed as a SERS substrate to distinguish between filtrate parts of the blood serum of HBV patients and healthy individuals based on their specific SERS peaks. The SERS spectral features associated with the filtrate parts of HBV patients' blood serum are well differentiated from the healthy volunteers. Principle component analysis (PCA) was applied on the SERS spectral data sets of HBV patients and healthy individuals and found extremely beneficial for the classification of their SERS spectral groups. Moreover, partial least square regression analysis (PLSR) has shown excellent performance in the quantitative analysis of the viral load values of the HBV patients using their SERS spectral data sets.
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