Gaussian numerical analysis and terahertz spectroscopic measurement of homocysteine

Identification of Panax notoginseng origin using terahertz precision spectroscopy and neural network algorithm

Panax notoginseng (P. notoginseng), a Chinese herb containing various saponins, benefits immune system in medicines development, which from Wenshan (authentic cultivation) is often counterfeited by others for large demand and limited supply. Here, we proposed a method for identifying P. notoginseng origin combining terahertz (THz) precision spectroscopy and neural network. Based on the comparative analysis of four qualitative identification methods, we chose high-performance liquid chromatography (HPLC) and THz spectroscopy to detect 252 samples from five origins. After classifications using Convolutional Neural Networks (CNNs) model, we found that the performance of THz spectra was superior to that of HPLC. The underlying mechanism is that there are clear nonlinear relations among the THz spectra and the origins due to the wide spectra and multi-parameter characteristics, which makes the accuracy of five-classification origin identification up to 97.62%. This study realizes the rapid, non-destructive and accurate identification of P. notoginseng origin, providing a practical reference for herbal medicine.

Machine Learning Enhanced Optical Spectroscopy for Disease Detection

Optical spectroscopy plays an important role in disease detection. Improving the sensitivity and specificity of spectral detection has great importance in the development of accurate diagnosis. The development of artificial intelligence technology provides a great opportunity to improve the detection accuracy through machine learning methods. In this Perspective, we focus on the combination of machine learning methods with the optical spectroscopy methods widely used for disease detection, including absorbance, fluorescence, scattering, FTIR, terahertz, etc. By comparing the spectral analysis with different machine learning methods, we illustrate that the support vector machine and convolutional neural network are most effective, which have potential to further improve the classification accuracy to distinguish disease subtypes if these machine learning methods are used. This Perspective broadens the scope of optical spectroscopy enhanced by machine learning and will be useful for the development of disease detection.

Measurement and Modeling of the Optical Properties of Adipose Tissue in the Terahertz Range: Aspects of Disease Diagnosis

In this paper, the measurement and modeling of optical properties in the terahertz (THz) range of adipose tissue and its components with temperature changes were performed. Spectral measurements were made in the frequency range 0.25-1 THz. The structural models of main triglycerides of fatty acids are constructed using the B3LYP/6-31G(d) method and the Gaussian03, Revision B.03 program. The optical density (OD) of adipose tissue samples decreases as temperature increases, which can be associated mostly with the dehydration of the sample. Some inclusion of THz wave scattering suppression into the OD decrease can also be expected due to refractive index matching provided by free fatty acids released from adipocytes at thermally induced cell lipolysis. It was shown that the difference between the THz absorption spectra of water and fat makes it possible to estimate the water content in adipose tissue. The proposed model was verified on the basis of molecular modeling and a comparison with experimental data for terahertz spectra of adipose tissue during its heating. Knowing the exact percentage of free and bound water in adipose tissue can help diagnose and monitor diseases, such as diabetes, obesity, and cancer.

Characterization of the remediation of chromium ion contamination with bentonite by terahertz time-domain spectroscopy

Heavy metal pollution of agricultural and urban soils limits economic progress in the rapidly developing society. Terahertz technology is applied to detect heavy metal pollutants under existence of multiple pathways of their dissemination. In this study, terahertz time-domain spectroscopy (THz-TDS) is employed as an advanced probing technique in combination with traditional detecting methods to measure the adsorption ability of trivalent chromium ions on bentonite. The concentration of chromium ions and the weight of bentonite are known to influence on the adsorption capacity of the latter. It is tested here by both qualitative and quantitative measurements of two mentioned parameters. The adsorption process of chromium ions by bentonite is monitored using THz-TDS. The adsorptions signal from samples at 0.5 THz gradually increases with the increase of bentonite weight or chromium ion concentration. It would appear to indicate that terahertz could be used for quantitative detection of metal ions. Secondly, the ratios of results obtained by inductively coupled plasma mass spectrometry (ICP-MS) and the THz-TDS ones are stabilized at 0.105  ±  0.014 as the bentonite weight or chromium ion concentration increase. Such finding confirms that terahertz technology can be used for the quantitative detection of metal ions. Using the relationship between the ICP-MS test results and the THz-TDS ones, the amplitude value of bentonite is obtained to be 13.925 at the concentration of chromium ions of 0.05 mol/L, the mass of bentonite sample involved in adsorption of 1.5 g, and the detection frequency in THz-TDS measurements of 0.5 THz. The adsorption coefficient of bentonite is calculated to be 1.44%. Increase of the chromium ion concentration to 0.2 mol/L, and the mass of bentonite involved in adsorption to 3 g leads to the increase of the amplitude corresponding to adsorbed chromium ions to about 19.463, and the adsorption coefficient to about 2.1%. Obtained results demonstrate that terahertz technology is promising to meet the ever-increasing requirements in mineral analyses for rapid detection of chemical contaminants and measurement of the adsorption efficiencies of materials.

Quantitative Analysis of Industrial Solid Waste Based on Terahertz Spectroscopy

Industrial solid waste refers to the solid waste that is produced in industrial production activities. Without correct treatment and let-off, industrial solid waste may cause environmental pollution due to a variety of pollutants and toxic substances that are contained in it. Conventional detection methods for identifying harmful substances are high performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS), which are complicated, time-consuming, and highly demanding for the testing environment. Here, we propose a method for the quantitative analysis of harmful components in industrial solid waste by using terahertz (THz) spectroscopy combined with chemometrics. Pyrazinamide, benazepril, cefprozil, and bisphenol A are four usual hazardous components in industrial solid waste. By comparing with the Raman method, the THz method shows a much higher accuracy for their concentration analysis (90.3–99.8% vs. 11.7–86.9%). In addition, the quantitative analysis of mixtures was conducted, and the resulting prediction accuracy rate was above 95%. This work has high application value for the rapid, accurate, and low-cost detection of industrial solid waste.

Qualitative and quantitative recognition of chiral drugs based on terahertz spectroscopy

Chiral drugs are drugs with chiral or asymmetric centres in their molecular structure. Different enantiomers of the same chiral drug have noticeably different pharmacological activities and pharmacokinetic properties. However, its distinction has been perplexing scholars for many years in the qualitative and quantitative detection of antagonistic drugs. Conventional detection methods, such as polarimetry, circular dichroism, and high-performance liquid chromatography, are time consuming, cause sample loss and have cumbersome operations, and they can be applied only to the sampling method. In this paper, we propose a fast, accurate, qualitative and quantitative method for the study of chiral drugs based on linearly polarized terahertz (THz) spectroscopy and imaging technology. Taking ibuprofen as an example, based on the THz absorption spectra of the enantiomers RS-ibuprofen, (R)-(-)-ibuprofen, and (S)-(+)-ibuprofen, their characteristic peak frequencies, peak amplitude differences and peak area differences were extracted to qualitatively and quantitatively distinguish and identify the three substances. THz spectral imaging provides more intuitive results than those obtained from previous methods. In quantitative identification, the stability and detection accuracy of THz spectroscopy are much greater than those of Raman spectroscopy (88.8-99.8% vs. 21.42-94.62%, respectively). The qualitative recognition accuracy was 100%, and the quantitative recognition standard deviation was less than 0.01, and it is also a non-destructive testing method. Furthermore, the above method combined with principal component analysis (PCA) and the support vector machine (SVM) neural network classification algorithm was applied to the analysis of other chiral drugs. These results are significant for the rapid, accurate and non-destructive identification of chiral drugs.

Terahertz Imaging and Spectroscopy in Cancer Diagnostics: A Technical Review

Terahertz (THz) waves are electromagnetic waves with frequency in the range from 0.1 to 10 THz. THz waves have great potential in the biomedical field, especially in cancer diagnosis, because they exhibit low ionization energy and can be used to discern most biomolecules based on their spectral fingerprints. In this paper, we review the recent progress in two applications of THz waves in cancer diagnosis: imaging and spectroscopy. THz imaging is expected to help researchers and doctors attain a direct intuitive understanding of a cancerous area. THz spectroscopy is an efficient tool for component analysis of tissue samples to identify cancer biomarkers. Additionally, the advantages and disadvantages of the developed technologies for cancer diagnosis are discussed. Furthermore, auxiliary techniques that have been used to enhance the spectral signal-to-noise ratio (SNR) are also reviewed.

Molecular methylation detection based on terahertz metamaterial technology

Terahertz wave has a good ability to identify biomolecules due to its fingerprint spectrum characteristics. However, the minimum detectable limit of terahertz technology by the conventional tablet pressing method is on the order of milligrams, which cannot meet the application requirements of low concentration detection in the biomedical field-near or below micrograms. Here, we proposed a method to enhance the detection sensitivity by designing a metamaterial chip with the absorption-induced transparency (AIT) effect, which can enhance the interaction between terahertz waves and biomolecules and lower the detectable limit. Taking 7-methylguanine (7-MG) as an example, based on its terahertz characteristic absorption peak, we designed a split-ring resonator (SRR) metamaterial chip, which has the advantages of high sensitivity, unlabeled detection, fast response and simple measurement. Its quantitative detection limit can reach 6.30 μg, which is about 500 times smaller than that of the traditional tablet pressing method (2.95 mg). In addition, for methylated and unmethylated substances, the chip exhibits different frequency shifts, which also realizes the qualitative identification effectively. These results provide a reference for the rapid and accurate diagnosis of diseases associated with molecular methylation in clinical medicine.

Quantitative analysis of homocysteine in liquid by terahertz spectroscopy

Homocysteine (C₄H₉NO₂S) is a variant of the amino acid cysteine, a harmful substance to the human body, which is closely related to cardiovascular disease, senile dementia, fractures, et al. At present, conventional methods for detecting homocysteine in biological samples include high performance liquid chromatography (HPLC), fluorescence polarization immunoassay (FPIA), and enzymatic cycling methods. These methods have the disadvantages of being time-consuming, sample-losing, chemical reagent-using and operation-cumbersome. Here, we present a method for the quantitative detection of homocysteine in liquid based on terahertz spectroscopy. Considering the strong absorption of water for terahertz beam, we also put forward a pretreatment method for drying samples at low temperature. These methods make the detection limit for homocysteine reach 10 µmol/L (human normal concentration). Based on the linear relationship between the homocysteine concentration and the THz spectral intensity, we can successfully achieve quantitative, accurate and real-time detection of homocysteine. As compared to Raman spectroscopy, the correlation coefficient of THz spectrum ( R 16.24 THz 2 = 0.99809) is much larger than that of the Raman spectrum ( R 2558.26 c m - 1 2  = 0.80022, R 2937.32 c m - 1 2 = 0.8028). These results are greatly useful for the accurate evaluation of pathological stage.

Quantitative analysis of direct oral anticoagulant rivaroxaban by terahertz spectroscopy

Rivaroxaban, as a direct oral anticoagulant, has been widely used in the treatment and prevention of thrombosis disease (TD). However, even if the same dose of rivaroxaban is taken, different pathophysiological characteristics of TD patients determine the differences in plasma concentrations between individuals, leading to the difficulties of dosage selection and plasma concentration control. Conventional rivaroxaban detection methods, including prothrombin time method, anti-Xa assay and liquid chromatography-tandem mass spectrometry (LC-MS/MS), are not widely used in clinical practice due to the limitations of accuracy, speed and cost. Here, we present a simple quantitative detection method for rivaroxaban by terahertz (THz) spectroscopy. Combining density functional theory (DFT) method and THz spectroscopy, the THz absorption peaks of rivaroxaban and the corresponding low-frequency vibrational modes are studied theoretically and experimentally. We find linear relationships between the amplitudes of these characteristic peaks and the concentrations of rivaroxaban. Based on these linear functions, we can analyse the rivaroxaban concentration with a detection time of 1 minute per test and the lowest detection limit of 2 μmol mL^-1. As compared to Raman spectroscopy method (its detection limit is about 80 μmol mL^-1), our method has more potential and is practical for the clinical quantitative detection of rivaroxaban as well as other direct oral anticoagulants.

Mid-infrared Lasers for Medical Applications: introduction to the feature issue

This feature issue contains a series of papers that report the most recent advances in the field of mid-infrared light sources used for medical applications, including tissue imaging, reconstruction, excision, and ablation. Many biomolecular compounds have strong resonances in the mid-infrared region and medicine is ideally suited to exploit this. The precision, sterility, and versatility of light in mid-infrared is opening more opportunities and this feature issue captures some of the most exciting.