Self-referenced Digital Spectral Chromatic Local Surface Plasmon Resonance in Ultrasensitive Severe Sepsis Interleukin-6 Detection

Clinical monitoring of cytokines, such as interleukin-6 (IL-6), enables a timely diagnosis and can significantly improve patient prognosis. In this study, we developed a rapid, label-free, ultrasensitive, and low matrix-effect method called chromatic digital nanoplasmon-metry (cDiNM) to detect IL-6 in human blood plasma. Utilizing a multiple filter configuration, two nonadjacent specific transmission wavelength bands are extracted. One is centered within the full-width-at-half-maximum (fwhm) range where the local surface plasmon resonance (LSPR) response of the 80 nm gold nanoparticles (AuNPs) is strongest, while the other band is narrowed and blue-shifted from the peak to a region with minor intensity change. Scattering images of AuNPs passing through these two bands are then captured simultaneously and independently via the red and green channels of a color scientific complementary metal-oxide-semiconductor (sCMOS) camera. This configuration allows every AuNPs' spectral chromatic image contrast to be a self-referenced subtractive analysis LSPR and facilitates evaluation of their changes induced by the IL-6 binding across numerous individual AuNPs. This method achieves IL-6 detection in blood plasma within 45 min, requiring only 0.5 mL of a 10-fold diluted, label-free sample, with a limit of detection and quantification (LOD and LOQ) of less than 19.2 and 87.8 fg/mL, respectively, and a recovery rate of 96%. In summary, cDiNM provides rapid and accurate IL-6 monitoring with promising potential for clinical application in sepsis patient care.

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Publication Details

Journal
ACS Sensors
Published
2025-02-05
DOI
https://doi.org/10.1021/acssensors.4c03067
Citations
1
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
0.67

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article

Self-referenced Digital Spectral Chromatic Local Surface Plasmon Resonance in Ultrasensitive Severe Sepsis Interleukin-6 Detection

Kwk Yeung, Sheng‐Hann Wang, Pei‐Kuen Wei, Ting-Wei Chang et al.
1 citations
ACS Sensors
Biosensors and Analytical Detection
0.67
article

Self-referenced Digital Spectral Chromatic Local Surface Plasmon Resonance in Ultrasensitive Severe Sepsis Interleukin-6 Detection

Kwk Yeung, Sheng‐Hann Wang, Pei‐Kuen Wei, Ting-Wei Chang, T. J. Chuang
article en
1 citations

Abstract

Clinical monitoring of cytokines, such as interleukin-6 (IL-6), enables a timely diagnosis and can significantly improve patient prognosis. In this study, we developed a rapid, label-free, ultrasensitive, and low matrix-effect method called chromatic digital nanoplasmon-metry (cDiNM) to detect IL-6 in human blood plasma. Utilizing a multiple filter configuration, two nonadjacent specific transmission wavelength bands are extracted. One is centered within the full-width-at-half-maximum (fwhm) range where the local surface plasmon resonance (LSPR) response of the 80 nm gold nanoparticles (AuNPs) is strongest, while the other band is narrowed and blue-shifted from the peak to a region with minor intensity change. Scattering images of AuNPs passing through these two bands are then captured simultaneously and independently via the red and green channels of a color scientific complementary metal-oxide-semiconductor (sCMOS) camera. This configuration allows every AuNPs' spectral chromatic image contrast to be a self-referenced subtractive analysis LSPR and facilitates evaluation of their changes induced by the IL-6 binding across numerous individual AuNPs. This method achieves IL-6 detection in blood plasma within 45 min, requiring only 0.5 mL of a 10-fold diluted, label-free sample, with a limit of detection and quantification (LOD and LOQ) of less than 19.2 and 87.8 fg/mL, respectively, and a recovery rate of 96%. In summary, cDiNM provides rapid and accurate IL-6 monitoring with promising potential for clinical application in sepsis patient care.

ACS SensorsVol. 10(2)
National Taipei University of Technology (TW), National Tsing Hua University (TW), Research Center for Applied Science, Academia Sinica (TW), Academia Sinica (TW)
Academia Sinica, National Tsing Hua University, National Taipei University of Technology, National Science and Technology Council
Openalex Percentile: Top 35%
Biosensors and Analytical Detection
0.67
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