Quantification of resistant starch content in rice after hydrothermal treatments using terahertz spectroscopy.

Since hydrothermal treatments can enhance resistant starch (RS) content in rice and provide health benefits when consumed, a less laborious and non-destructive method to determine RS content is needed. Terahertz (THz) spectroscopy is hypothesized as a suitable method to quantify RS content in rice after hydrothermal treatment with its sensitivity for the intermolecular forces increase in the formation of RS. In this study, we first used the traditional in vitro hydrolysis method to determine the content of RS in rice. Then, the potential of starch absorbance peaks to quantify RS content after three commonly used hydrothermal methods, soaking, mild heat-moisture treatment, and parboiling, was investigated. The second derivative intensities of the peak at 9.0, 10.5, 12.1, and 13.1 THz were confirmed as being correlated with RS content and showed the high accuracy to predict RS content in samples (R2 > 0.96). Our results indicate the RS content of hydrothermally treated rice can be accurately quantified using these peaks.

Ensemble learning prediction framework for EGFR amplification status of glioma based on terahertz spectral features.

Epidermal growth factor receptor (EGFR) plays a pivotal role in the initiation and progression of gliomas. In particular, in glioblastoma, EGFR amplification emerges as a catalyst for invasion, proliferation, and resistance to radiotherapy and chemotherapy. Current approaches are not capable of providing rapid diagnostic results of molecular pathology. In this study, we propose a terahertz spectroscopic approach for predicting the EGFR amplification status of gliomas for the first time. A machine learning model was constructed using the terahertz response of the measured glioma tissues, including the absorption coefficient, refractive index, and dielectric loss tangent. The novelty of our model is the integration of three classical base classifiers, i.e., support vector machine, random forest, and extreme gradient boosting. The ensemble learning method combines the advantages of various base classifiers, this model has more generalization ability. The effectiveness of the proposed method was validated by applying an individual test set. The optimal performance of the integrated algorithm was verified with an area under the curve (AUC) maximum of 85.8 %. This signifies a significant stride toward more effective and rapid diagnostic tools for guiding postoperative therapy in gliomas.

Qualitative and Quantitative Detection of Typical Reproductive Hormones in Dairy Cows Based on Terahertz Spectroscopy and Metamaterial Technology.

Progesterone (PROG) and estrone (E1) are typical reproductive hormones in dairy cows. Assessing the levels of these hormones in vivo can aid in estrus identification. In the present work, the feasibility of the qualitative and quantitative detection of PROG and E1 using terahertz time-domain spectroscopy (THz-TDS) and metamaterial technology was preliminarily investigated. First, the time domain spectra, frequency domain spectra, and absorption coefficients of PROG and E1 samples were collected and analyzed. A vibration analysis was conducted using density functional theory (DFT). Subsequently, a double-ring (DR) metamaterial structure was designed and simulated using the frequency domain solution algorithm in CST Studio Suite (CST) software. This aimed to ensure that the double resonance peaks of DR were similar to the absorption peaks of PROG and E1. Finally, the response of DR to different concentrations of PROG/E1 was analyzed and quantitatively modeled. The results show that a qualitative analysis can be conducted by comparing the corresponding DR resonance peak changes in PROG and E1 samples at various concentrations. The best R2 for the PROG quantitative model was 0.9872, while for E1, it was 0.9828. This indicates that terahertz spectral-metamaterial technology for the qualitative and quantitative detection of the typical reproductive hormones PROG and E1 in dairy cows is feasible and worthy of in-depth exploration. This study provides a reference for the identification of dairy cow estrus.

Metal-Graphene Hybrid Terahertz Metasurfaces for Circulating Tumor DNA Detection Based on Dual Signal Amplification.

Terahertz (THz) spectroscopy has impressive capability for label-free biosensing, but its utility in clinical laboratories is rarely reported due to often unsatisfactory detection performances. Here, we fabricated metal-graphene hybrid THz metasurfaces (MSs) for the sensitive and enzyme-free detection of circulating tumor DNA (ctDNA) in pancreatic cancer plasma samples. The feasibility and mechanism of the enhanced effects of a graphene bridge across the MS and amplified by gold nanoparticles (AuNPs) were investigated experimentally and theoretically. The AuNPs serve to boost charge injection in the graphene film and result in producing a remarkable change in the graded transmissivity index to THz radiation of the MS resonators. Assay design utilizes this feature and a cascade hybridization chain reaction initiated on magnetic beads in the presence of target ctDNA to achieve dual signal amplification (chemical and optical). In addition to demonstrating subfemtomolar detection sensitivity and single-nucleotide mismatch selectivity, the proposed method showed remarkable capability to discriminate between pancreatic cancer patients and healthy individuals by recognizing and quantifying targeted ctDNAs. The introduction of graphene to the metasurface produces an improved sensitivity of 2 orders of magnitude for ctDNA detection. This is the first study to report the combined application of graphene and AuNPs in biosensing by THz spectroscopic resonators and provides a combined identification scheme to detect and discriminate different biological analytes, including nucleic acids, proteins, and various biomarkers.

Dielectric Response of Different Alcohols in Water-Rich Binary Mixtures from THz Ellipsometry.

We report a study on the hydrogen bonding mechanisms of three aliphatic alcohols (2-propanol, methanol, and ethanol) and one diol (ethylene glycol) in water solution using a time-domain ellipsometer in the THz region. The dielectric response of the pure liquids is nicely modeled by the generalized Debye-Lorentz equation. For binary mixtures, we analyze the data using a modified effective Debye model, which considers H-bond rupture and reformation dynamics and the motion of the alkyl chains and of the OH groups. We focus on the properties of the water-rich region, finding anomalous behavior in the absorption properties at very low solute molar concentrations. These results, first observed in the THz region, are in line with previous findings from different experiments and can be explained by taking into account the amphiphilic nature of the alcohol molecules.

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.

Characteristic fingerprint spectrum of α-synuclein mutants on terahertz time-domain spectroscopy.

α-Synuclein, a presynaptic neuronal protein encoded by the SNCA gene, is involved in the pathogenesis of Parkinson's disease. Point mutations and multiplications of α-synuclein (A30P and A53T) are correlated with early-onset Parkinson's disease characterized by rapid progression and poor prognosis. Currently, the clinical identification of SNCA variants, especially disease-related A30P and A53T mutants, remains challenging and also time consuming. This study aimed to develop a novel label-free detection method for distinguishing the SNCA mutants using transmission terahertz (THz) time-domain spectroscopy. The protein was spin-coated onto the quartz to form a thin film, which was measured using THz time-domain spectroscopy. The spectral characteristics of THz broadband pulse waves of α-synuclein protein variants (SNCA wild type, A30P, and A53T) at different frequencies were analyzed via Fourier transform. The amplitude A intensity (AWT, AA30P, and AA53T) and peak occurrence time in THz time-domain spectroscopy sensitively distinguished the three protein variants. The phase φ difference in THz frequency domain followed the trend of φWT > φA30P > φA53T. There was a significant difference in THz frequency amplitude A' corresponding to the frequency ranging from 0.4 to 0.66 THz (A'A53T > A'A30P > A'WT). At a frequency of 0.4-0.6 THz, the transmission T of THz waves distinguished three variants (TA53T > TA30P > TWT), whereas there was no difference in the transmission T at 0.66 THz. The SNCA wild-type protein and two mutant variants (A30P and A53T) had distinct characteristic fingerprint spectra on THz time-domain spectroscopy. This novel label-free detection method has great potential for the differential diagnosis of Parkinson's disease subtypes.

Correlation between Hydration States and Self-assembly Structures of Phospholipid and Surfactant Studied by Terahertz Spectroscopy.

Phospholipids and surfactants form membranes and other self-assembled structures in water. However, it is not fully understood how the surrounding water (hydration water) is involved in their structure formation. In this paper, I summarize the results of our investigation of the long-range hydration state of phospholipids and surfactants at their surfaces by means of terahertz spectroscopy. By observing the collective rotational dynamics of water in the picosecond time scale, this technique allows us to observe not only the water directly bound to the solute, but also the weakly affected water outside of it. For example, PC phospholipids inhibit water dynamics over long distances, whereas PE phospholipids make water more mobile than bulk water. The causes of this difference in hydration and how it is involved in the structural formation of the membrane are reviewed.

Terahertz spectra reconstructed using convolutional denoising autoencoder for identification of rice grains infested with Sitophilus oryzae at different growth stages.

Rice grains are often infected by Sitophilus oryzae due to improper storage, resulting in quality and quantity losses. The efficacy of terahertz time-domain spectroscopy (THz-TDS) technology in detecting Sitophilus oryzae at different stages of infestation in stored rice was employed in the current research. Terahertz (THz) spectra for rice grains infested by Sitophilus oryzae at different growth stages were acquired. Then, the convolutional denoising autoencoder (CDAE) was used to reconstruct THz spectra to reduce the noise-to-signal ratio. Finally, a random forest classification (RFC) model was developed to identify the infestation levels. Results showed that the RFC model based on the reconstructed second-order derivative spectrum with an accuracy of 84.78%, a specificity of 86.75%, a sensitivity of 86.36% and an F1-score of 85.87% performed better than the original first-order derivative THz spectrum with an accuracy of 89.13%, a specificity of 91.38%, a sensitivity of 88.18% and an F1-score of 89.16%. In addition, the convolutional layers inside the CDAE were visualized using feature maps to explain the improvement in results, illustrating that the CDAE can eliminate noise in the spectral data. Overall, THz spectra reconstructed with the CDAE provided a novel method for effective THz detection of infected grains.

Comprehensive Similarity Algorithm and Molecular Dynamics Simulation-Assisted Terahertz Spectroscopy for Intelligent Matching Identification of Quorum Signal Molecules (N-Acyl-Homoserine Lactones).

To investigate the mechanism of aquatic pathogens in quorum sensing (QS) and decode the signal transmission of aquatic Gram-negative pathogens, this paper proposes a novel method for the intelligent matching identification of eight quorum signaling molecules (N-acyl-homoserine lactones, AHLs) with similar molecular structures, using terahertz (THz) spectroscopy combined with molecular dynamics simulation and spectral similarity calculation. The THz fingerprint absorption spectral peaks of the eight AHLs were identified, attributed, and resolved using the density functional theory (DFT) for molecular dynamics simulation. To reduce the computational complexity of matching recognition, spectra with high peak matching values with the target were preliminarily selected, based on the peak position features of AHL samples. A comprehensive similarity calculation (CSC) method using a weighted improved Jaccard similarity algorithm (IJS) and discrete Fréchet distance algorithm (DFD) is proposed to calculate the similarity between the selected spectra and the targets, as well as to return the matching result with the highest accuracy. The results show that all AHL molecular types can be correctly identified, and the average quantization accuracy of CSC is 98.48%. This study provides a theoretical and data-supported foundation for the identification of AHLs, based on THz spectroscopy, and offers a new method for the high-throughput and automatic identification of AHLs.

Vibrational spectroscopic detection and analysis of salicylic acid and aspirin binary cocrystal.

Salicylic acid is a raw material for preparing aspirin and holds an important position in medical history. Studying the crystallization of these two drugs is of great significance in improving their dissolution rate, bioavailability, and physical stability. Although various techniques have been used for structural characterization, there is still a lack of information on the collective vibrational behavior of aspirin and salicylic acid eutectic compounds. Firstly, two starting materials (salicylic acid and aspirin) were ground in a 1:1 M ratio to prepare eutectic compounds. The eutectic composition was studied using vibrational spectroscopy techniques, such as X-ray powder diffusion (XRPD), terahertz time-domain spectroscopy (THz-TDS), and Raman spectroscopy. Additionally, the structure of the aspirin and salicylic acid eutectic was simulated and optimized using density functional theory. It was found that the eutectic type II was the most consistent with the experiment, and the corresponding vibration modes of each peak were provided. These results offer a unique method for characterizing the structural composition of eutectic crystals, which can be utilized to enhance the physical and chemical properties, as well as the pharmacological activity, of specific drugs at the molecular level.

Application of terahertz Time-Domain spectroscopy and chemometrics-based whale optimization algorithm in PDE5 inhibitor detection.

Combating the illicit use of PDE5 inhibitor drugs is a focal point in forensic science research. In order to achieve rapid identification of such drugs, this study applies terahertz time-domain spectroscopy combined with chemometrics to establish a fast and accurate detection method for PDE5 inhibitors. The optimal detection method is determined by comparing the spectral performance of three optical parameters, namely absorption coefficient, refractive index, and dielectric constant. Linear discriminant models based on different spectral parameters, whale optimization algorithm optimized extreme learning machine models, and whale optimization algorithm optimized random forest models are established. The effectiveness and performance of principal component analysis and competitive adaptive reweighted sampling algorithm for spectral feature data selection are also investigated. The PDE5 inhibitor identification model based on the competitive adaptive reweighted sampling - whale optimization algorithm - random forest (CARS-WOA-RF) model achieves an accuracy of 98.61%, and the identification model for two concentrations of Sildenafil achieves 100% accuracy. The results demonstrate that terahertz time-domain spectroscopy combined with chemometrics can effectively detect various common types of PDE5 inhibitor drugs and different concentrations.

An innovative detection technique for capillary electrophoresis: Localized terahertz emission-time domain spectroscopy.

Terahertz (THz) time-domain spectroscopy (TDS) is a recently emerging analysis method which can provide unique information on molecular vibration and rotation induced by inter/intra-molecular interactions. Although the application of THz-TDS to high-performance microscale separation methods like capillary electrophoresis (CE) has been anticipated, it has been hindered due to the diffraction limit of THz wave (typically, hundreds µm). In order to realize CE-THz-TDS, in this study, we placed a narrow open-tubular capillary on the surface of a GaAs semiconductor substrate as a "localized" THz-emitter. By focusing femtosecond pulsed laser beams at the surface of a gallium arsenide (GaAs) substrate closest to the capillary, THz waves were locally generated to pass through the capillary, so that THz absorbance spectra were obtained from the capillary which has narrower inner diameter than the diffraction limit. As a typical result from acetic acid analysis in the CE-THz-TDS platform, information on the refractive index and extinction coefficient was obtained, which showed non-linear and linear concentration dependence, respectively, similar to conventional THz-TDS using large liquid cells. Finally, CE-THz-TDS analysis of several carboxylic acids was demonstrated. Two acids were successfully separated and detected with THz-TDS, where their electrophoretic mobility values were estimated as close to those obtained with conventional contactless conductivity detection. Our proposed CE-THz-TDS showed the potential for the systematic analysis of inter/intra-molecular weak interactions like hydrogen bonds, which are unable to obtain with conventional detectors.

Terahertz Attenuated Total Reflection Spectral Response and Signal Enhancement via Plasmonic Enhanced Sensor for Eye Drop Detection.

With chronic ocular diseases such as glaucoma and dry eye syndrome, patients have to apply eye drops over the long term. The therapeutic effects of eye drops depend on the amount of drug contained and the stability of the solution. In addition, contamination during usage and transport can also negatively affect the quality and efficacy of eye drops. The current techniques for the characterization of eye drops are often complicated and time-consuming. Developing a fast and non-invasive way of accurately measuring eye drop quality remains an ongoing challenge. The biggest challenge and primary prerequisite for the application of this new detection technique for eye drops is the obtention of a sufficient spectral response and resolvable signal, considering the large background signal contributed by water. In this work, we use terahertz (THz) attenuated total reflection (ATR) spectroscopy combined with a sensitive hybrid graphene oxide (GO) and carbon nanotube (CNT) thin-film sensors to obtain distinct THz spectral signals in commercial eye drops. Various commercial eye drop products have been tested, and we show that they can be differentiated via their spectral signals. Our results provide a solid foundation for the future fine analysis of eye drops and the detection of their quality. Furthermore, THz spectroscopy combined with GO/CNT films has significant potential and advantages for the non-destructive characterization of aqueous pharmaceutical products.

Deep-Learning Terahertz Single-Cell Metabolic Viability Study.

Cell viability assessment is critical, yet existing assessments are not accurate enough. We report a cell viability evaluation method based on the metabolic ability of a single cell. Without culture medium, we measured the absorption of cells to terahertz laser beams, which could target a single cell. The cell viability was assessed with a convolution neural classification network based on cell morphology. We established a cell viability assessment model based on the THz-AS (terahertz-absorption spectrum) results as y = a = (x - b)c, where x is the terahertz absorbance and y is the cell viability, and a, b, and c are the fitting parameters of the model. Under water stress the changes in terahertz absorbance of cells corresponded one-to-one with the apoptosis process, and we propose a cell 0 viability definition as terahertz absorbance remains unchanged based on the cell metabolic mechanism. Compared with typical methods, our method is accurate, label-free, contact-free, and almost interference-free and could help visualize the cell apoptosis process for broad applications including drug screening.

Optimal frequency determination for terahertz technology-based detection of colitis-related cancer in mice.

Colorectal cancer is a prevalent malignancy globally, often linked to chronic colitis. Terahertz technology, with its noninvasive and fingerprint spectroscopic properties, holds promise in disease diagnosis. This study aimed to explore terahertz technology's application in colitis-associated cancer using a mouse model. Mouse colorectal tissues were transformed into paraffin-embedded blocks for histopathological analysis using HE staining. Terahertz transmission spectroscopy was performed on the tissue blocks. By comparing terahertz absorption differences, specific frequency bands were identified as optimal for distinguishing cancerous and normal tissues. The study revealed that terahertz spectroscopy effectively differentiates colitis-related cancers from normal tissues. Remarkably, 1.8 THz emerged as a potential optimal frequency for diagnosing colorectal cancer in mice. This suggests the potential for rapid histopathological diagnosis of colorectal cancer using terahertz technology.

Analyzing the effects of nonthermal pretreatments on the quality of microwave vacuum dehydrated beef using terahertz time-domain spectroscopy and near-infrared hyperspectral imaging.

Both nonthermal pretreatment and nondestructive analysis are effective technologies in improving drying processes. This study evaluated the effects of different pretreatment methods on the quality of beef dehydrated by microwave vacuum drying (MVD) and compared the MVD process performance comprising real-time moisture content (MC), MC loss, colour content, and shrinkage rate using different optical sensing methods including terahertz time-domain spectroscopy (THz-TDS) and near-infrared hyperspectral imaging (NIR-HSI). Results indicated that osmotic pretreatment improved the drying rate of MVD beef with lower changes in colour and shrinkage rate. Both THz-TDS-based and NIR-HSI-based on-site direct scanning and in-situ in-direct sensing showed accurate prediction results, with best R2p of 0.9646 and 0.9463 for MC and R2p of 0.9817 and 0.9563 for MC loss prediction, respectively. NIR-HSI visualisation of MC results showed that ultrasound pretreatment curbed but osmotic pretreatment promoted nonuniform distribution during MVD. This research should guide improving the industrial MVD drying process.

Application of IRI Visualization to Terahertz Vibrational Spectroscopy of Hydroxybenzoic Acid Isomers.

The characteristic absorption spectra of three positional isomers of hydroxybenzoic acid are measured using a terahertz time-domain spectroscopy system (THz-TDS) in the 0.6-2.0 THz region at room temperature. Significant differences in their terahertz spectra are discovered, which indicates that THz-TDS is an effective means to identify positional isomers. In order to simulate their spectra, the seven molecular clusters of 2-, 3-, and 4-hydroxybenzoic acid (2-, 3-, and 4-HA) are calculated using the DFT-D3 method. Additionally, the potential energy distribution (PED) method is used to analyze their vibration modes. The analysis indicates that the vibration modes of 2-HA are mainly out-of-plane angle bending and bond angle bend in plane. The vibration modes of 3-HA are mainly bond length stretch and dihedral angle torsion. The vibration modes of 4-HA are mainly bond angle bend in plane and dihedral angle torsion. Interaction region indicator (IRI) analysis is used to visualize the location and type of intermolecular interactions in 2-, 3-, and 4-HA crystals. The results show that the weak interaction type of 2-, 3-, and 4-HA is dominated by van der Waals (vdW) interaction. Therefore, we can confirm that terahertz spectroscopy detection technology can be used as an effective means to identify structural isomers and detect the intermolecular interactions in these crystals. In addition, it can explain the absorption mechanism of terahertz waves interacting with matter.

Investigating the function and design of molecular materials through terahertz vibrational spectroscopy.

Terahertz spectroscopy has proved to be an essential tool for the study of condensed phase materials. Terahertz spectroscopy probes the low-frequency vibrational dynamics of atoms and molecules, usually in the condensed phase. These nuclear dynamics, which typically involve displacements of entire molecules, have been linked to bulk phenomena ranging from phase transformations to semiconducting efficiency. The terahertz region of the electromagnetic spectrum has historically been referred to as the 'terahertz gap', but this is a misnomer, as there exist a multitude of methods for accessing terahertz frequencies, and now there are cost-effective instruments that have made terahertz studies much more user-friendly. This Review highlights some of the most exciting applications of terahertz vibrational spectroscopy so far, and provides an in-depth overview of the methods of this technique and its utility to the study of the chemical sciences.

Estimating Thoracic Movement with High-Sampling Rate THz Technology.

We use a high-sampling rate terahertz (THz) homodyne spectroscopy system to estimate thoracic movement from healthy subjects performing breathing at different frequencies. The THz system provides both the amplitude and phase of the THz wave. From the raw phase information, a motion signal is estimated. An electrocardiogram (ECG) signal is recorded with a polar chest strap to obtain ECG-derived respiration information. While the ECG showed sub-optimal performance for the purpose and only provided usable information for some subjects, the signal derived from the THz system showed good agreement with the measurement protocol. Over all the subjects, a root mean square estimation error of 1.40 BPM is obtained.