ABSTRACT
Accurate characterization of biological matter, for example, in tissue, cells, and biological fluids, is of high importance. For example, early and correct detection of abnormalities, such as cancer, is essential as it enables early and effective type-specific treatment, which is crucial for mortality reduction [1]. Moreover, it is imperative to investigate the effectiveness and toxicity of pharmaceutical treatments before administration in clinical practice [2]. However, biological matter characterization still faces many challenges. State-of-the-art imaging and characterization methods have drawbacks, such as the requirement to attach difficult-to-find and costly labels to the biological target (e.g., COVID-19 rapid tests), expensive equipment (e.g., magnetic resonance imaging), low accuracy (e.g., ultrasound), use of ionizing radiation (e.g., X-rays), and invasiveness [3]. The characterization of biological matter using microwave (μW), millimeter-wave (mmW), and terahertz (THz) spectroscopy is a promising alternative: it is label-free, does not require ionizing radiation, and can be noninvasive. Moreover, there is a significant difference in how different biological materials absorb, reflect, and transmit electromagnetic (EM) waves [4] that is due to the difference in their dielectric properties. The dielectric properties are described by the frequency-dependent material parameter called the complex permittivity f, which expresses how the material responds to an external oscillating electric field. The complex permittivity of a material determines how the material absorbs, reflects, and transmits EM waves at different frequencies (Figure 1). Since each biological material's permittivity spectrum is different, it acts as an EM fingerprint. A material's complex permittivity can be calculated from the reflection and transmission of EM waves through the material, described by the S-parameters, which can be measured using a vector network analyzer (VNA) transmitting and receiving EM waves over a range of frequencies. The amplitude and phase of the transmitted and reflected EM waves at different frequencies are influenced by different underlying biological effects at different scales. That causes the entire spectrum to provide information from the supracellular to the molecular and even atomic scale. © 2000-2012 IEEE.
ABSTRACT
A metamaterial composed of diamond-shaped (70 μm X 35 μm) copper patches was designed and used to detect nanoparticles with 0.75-1.1 terahertz transmission spectroscopy. Deoxyribonucleic acid (DNA) bases adenine, thymine, cytosine, and guanine were detected and identified. Cytosine showed 1.7 dB higher absorption around 0.975 THz than the other bases. SARS-CoV-2 infected saliva showed different spectrum and -10 dB higher absorption than uninfected saliva over 0.75-1.1 THz. Other nanoparticles consisting of 100-500 nm antimony, carbon black, zeolite aluminosilicate molecular sieves), Terfenol-D (Tb0.3 Dy0.7Fe2), Cu2s,Ag2S, dust collected from bench tops, 10-100 μm size diamond particles, red polystyrene beads, iron particles and graphene sheets were also tested. Sensor sensitivity for uninfected saliva was 0.3 dB/ng and for infected saliva was 0.8 dB/ng. The metamaterial surface studied here enables detection of airborne particles larger than 10 μm in diameter. © 2022 IEEE.
ABSTRACT
Adhesion of the SARS-CoV-2 virus spike protein was studied by vibrational spectroscopy using terahertz metamaterials. Specific features of metastructure absorption by histidine, albumin, and receptor-binding domain of spike protein films were investigated. An original method for quantitative estimation of the efficiency of virus adhesion on the surface of metamaterials has been proposed and experimentally tested. © 2022 IEEE.
ABSTRACT
Infectious diseases are among the most severe threats to modern society. Current methods of virus infection detection based on genome tests need reagents and specialized laboratories. The desired characteristics of new virus detection methods are noninvasiveness, simplicity of implementation, real-time, low cost and label-free detection. There are two groups of methods for molecular biomarkers' detection and analysis: (i) a sample physical separation into individual molecular components and their identification, and (ii) sample content analysis by laser spectroscopy. Variations in the spectral data are typically minor. It requires the use of sophisticated analytical methods like machine learning. This review examines the current technological level of laser spectroscopy and machine learning methods in applications for virus infection detection.
Subject(s)
Lasers , Spectrum Analysis, Raman , Biomarkers , Spectrum Analysis, Raman/methodsABSTRACT
We propose a tested, sensitive, and prompt COVID-19 breath screening method that takes less than 1 min. The method is nonbiological and is based on the detection of a shift in the resonance frequency of a nanoengineered inductor-capacitor (LC) resonant metamaterial chip, caused by viruses and mainly related exhaled particles, when performing terahertz spectroscopy. The chip consists of thousands of microantennas arranged in an array and enclosed in a plastic breathalyzer-like disposable capsule kit. After an appreciable agreement between numerical simulations (COMSOL and CST) and experimental results was reached using our metamaterial design, low-scale clinical trials were conducted with asymptomatic and symptomatic coronavirus patients and healthy individuals. It is shown that coronavirus-positive individuals are effectively screened upon observation of a shift in the transmission resonance frequency of about 1.5-9 GHz, which is diagnostically different from the resonance shift of healthy individuals who display a 0-1.5 GHz shift. The initial results of screening coronavirus patients yielded 88% agreement with the realtime quantitative polymerase chain reaction (RT-qPCR) results (performed concurrently with the breath test) with an outcome of a positive predicted value of 87% and a negative predicted value of 88%.
ABSTRACT
Spectral properties of S and S1 spike proteins were studied using vibration spectroscopy methods. Also, vibration signatures of amino acids that make up the RGD, the part of S1 protein responsible for adhesion, were studied by Terahertz (THz) time-domain, Infrared (IR) and Raman spectroscopies in the low-frequency and in the fingerprint. THz metamaterials have been developed that increase the sensitivity of THz spectroscopy to the presence of both proteins. We have studied the spectra of amino acids, which play a role in the adhesion of proteins, on the metal surfaces of metamaterials, aluminum, and gold. Spectral differences were found between S and S1 proteins of SARS-CoV-2. The spectral differences between amino acids prepared in the form of thin films and in the form of bulk sample are discussed. © 2021 IEEE
ABSTRACT
Adhesion of the spike protein of the SARS-CoV-2 virus is studied by vibrational spectroscopy using terahertz metamaterials. The features of metastructure absorption upon the deposition of histidine, albumin, and the receptor-binding domain of the spike protein films are investigated. An original technique for quantitative assessment of the efficiency of virus adhesion on the metamaterial surfaces are proposed and experimentally tested.
ABSTRACT
Adhesion of the spike protein of the SARS-CoV-2 virus is studied by vibrational spectroscopy using terahertz metamaterials. The features of metastructure absorption upon the deposition of histidine, albumin, and the receptor-binding domain of the spike protein films are investigated. An original technique for quantitative assessment of the efficiency of virus adhesion on the metamaterial surfaces are proposed and experimentally tested. [ FROM AUTHOR] Copyright of Quantum Electronics is the property of IOP Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)