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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Do Infrared Molecular Fingerprints of Individuals Exist? Lessons from Spectroscopic Analysis of Human Blood
摘要： Genetic, lifestyle and environmental factors, along with development and aging impact molecular composition of human blood. Although many diseases leave their trace in blood, the question is whether this trace can be robustly and reproducibly measured and used for health monitoring of a given adult population. Infrared molecular spectra of blood serum can be obtained in a non-invasive, time- and cost-efficient manner, delivering molecular information from all molecular species within the highly complex samples. We demonstrate that broadband infrared spectroscopy can be used for reproducible molecular fingerprinting of human blood. To evaluate whether certain medium is sufficiently robust to facilitate detection of disease onset, the quantitative extent of variability of a person as well as a reference population needs to be evaluated. If within-person variability would exceed that of the between-personal variability in a reference population, the approach would not be suited for disease detection. To assess the extent of uniqueness of infrared molecular fingerprints as well as their biological variability, we performed a comprehensive prospective longitudinal study collecting blood samples of 27 healthy individuals donating blood at 8 consequent intervals. We apply broadband infrared molecular fingerprinting by Fourier transform infrared spectroscopy (FTIR) and analyse between-person and within-person variability based on all different molecular classes in the blood simultaneously. We report experimental evidence of the feasibility of identifying a person within a group of individuals based on her/his infrared molecular fingerprint, similarly to metabolic fingerprints [1]. In a first step, using standard methods for descriptive analysis we observe that the between-person variability is larger than the within-person variability by a factor of 3 (Fig.1 Left). This observation opens up the possibility for disease detection. In a second step, we combine standard dimensionality-reduction methods, such as principal component analysis (PCA), and several high-accuracy machine-learning algorithms [1] (random forests, extreme gradient boosting, k nearest neighbours) for deriving classification rules, which we then use for making predictions on test sets of unseen data. For a group of 7 donations that span a period of 6 weeks, we reach peak classification accuracy of above 95% (Fig.1 Right), while the accuracy of a classifier predicting in random would have been as low as 3.7%. In addition, we evaluate the underlying spectral features with respect to their importance on signalling separation and in this way identifying the human blood serum constituents associated with between-person variation. Observed robustness of infrared molecular fingerprints suggests their applicability for health and treatment monitoring.
关键词： infrared molecular fingerprints,FTIR,health monitoring,human blood,spectroscopic analysis
更新于2025-09-12 10:27:22
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - All-Dielectric High-Q Metasurfaces for Infrared Absorption Spectroscopy Applications
摘要： The mid-infrared (mid-IR) spectral range is crucial for spectroscopic investigations of biological systems since it contains the characteristic absorption signatures (i.e., the molecular ‘fingerprints’) of chemical and biological analytes, which are uniquely determined by the vibrational modes and associated absorption bands of its chemical bonds. Here we present a novel nanophotonics-based approach for detecting molecular fingerprints, which utilizes imaging-based methods to provide spectrometer-less operation in a miniaturized sensor device ideally suited for analyzing complex biological systems. The central building block of this technique is a pixelated dielectric metasurface where the individual metapixels are engineered to provide sharp resonances at a given resonance frequency. Each metapixel is made out of specifically designed zig-zag resonator arrays, which employ the concept of bound states in continuum to create high-Q resonances. The detection performance of the experimentally realized metasurface sensor was demonstrated by interrogating a monolayer of recombinant protein A/G molecules, which reveals the characteristic amide I and amide II absorption bands as distinct regions with attenuated peak reflectance of the resonances. A comparison of the total reflectance signals of all the metapixels before and after material adsorption delivers a distinct barcode pattern which can be used for chemically specific molecule detection. Importantly, this molecular barcoding method operates under broadband illumination and detection conditions, meaning that the chemically specific signals can be obtained without the need for spectrometry.
关键词： high-Q resonances,dielectric metasurface,nanophotonics,molecular barcoding,mid-infrared,molecular fingerprints
更新于2025-09-11 14:15:04