Molecular identification of bio-fluids in gas phase using infrared spectroscopy

Baseline correction for the infrared spectra of exhaled breath

Infrared spectroscopy appears to be a promising analytical method for the metabolic analysis of breath. However, due to the presence of trace amounts in exhaled breath, the absorption strength of the metabolites remains extremely low. In such low detection limits, the nonlinear detection sensitivity of the infrared detector and electronic noise strongly modify the baseline of the acquired infrared spectra of breath. Fitting the reference molecular spectra with the baseline-modified spectral features of breath metabolites does not provide accurate identification. Therefore, baseline correction of the acquired infrared spectra of breath is the primary requirement for the success of breath-based infrared diagnosis. A selective spectral region-based, simple baseline correction method is proposed for the infrared spectroscopy of breath.

Neonatal Exhaled Breath Sampling for Infrared Spectroscopy: Biomarker Analysis

Monitoring health conditions in neonates for early therapeutic intervention in case deviations from physiological conditions is crucial for their long-term development. Due to their immaturity preterm born neonates are dependent on particularly careful physical and neurological diagnostic methods. Ideally, these should be noninvasive, noncontact, and radiation free. Infrared spectroscopy was used to analyze exhaled breath from 71 neonates with a special emphasis on preterm infants, as a noninvasive, noncontact, and radiation-free diagnostic tool. Passive sample collection was performed by skilled clinicians. Depending on the mode of respiratory support of infants, four different sampling procedures were adapted to collect exhaled breath. With the aid of appropriate reference samples, infrared spectroscopy has successfully demonstrated its effectiveness in the analysis of breath samples of neonates. The discernible increase in concentrations of carbon dioxide, carbon monoxide, and methane in collected samples compared to reference samples served as compelling evidence of the presence of exhaled breath. With regard to technical hurdles and sample analysis, samples collected from neonates without respiratory support proved to be more advantageous compared to those obtained from intubated infants and those with CPAP (continuous positive airway pressure). The main obstacle lies in the significant dilution of exhaled breath in the case of neonates receiving respiratory support. Metabolic analysis of breath samples holds promise for the development of noninvasive biomarker-based diagnostics for both preterm and sick neonates provided an adequate amount of breath is collected.

Standard operating procedure to reveal prostate cancer specific volatile organic molecules by infrared spectroscopy

The growing number of prostate cancer cases is a real concern in modern society. Over 1.4 million new cases and about 400 thousand (>26%) deaths were registered worldwide in 2020 due to prostate cancer. The high mortality rate of prostate cancer is due to the lack of reliable early detection of the disease. Till now the most reliable diagnosis of cancer is tissue biopsy, which is an invasive process. A non-invasive or minimally invasive technique could lead to a diagnostic tool that will allow for saving or prolonging the lifespan of millions of lives. Metabolite-based diagnostics may have a better chance of early cancer detection. However, reliable detection techniques need to be developed. Infrared spectroscopy based gaseous-biofluid holds great promise towards the development of non-invasive diagnostics. A pilot study based on breath analysis by infrared spectroscopy showed promising results in distinguishing prostate cancer patients from healthy volunteers. Details of the spectral metabolic analysis are presented.

Non-Invasive Disease Specific Biomarker Detection Using Infrared Spectroscopy: A Review

Many life-threatening diseases remain obscure in their early disease stages. Symptoms appear only at the advanced stage when the survival rate is poor. A non-invasive diagnostic tool may be able to identify disease even at the asymptotic stage and save lives. Volatile metabolites-based diagnostics hold a lot of promise to fulfil this demand. Many experimental techniques are being developed to establish a reliable non-invasive diagnostic tool; however, none of them are yet able to fulfil clinicians' demands. Infrared spectroscopy-based gaseous biofluid analysis demonstrated promising results to fulfil clinicians' expectations. The recent development of the standard operating procedure (SOP), sample measurement, and data analysis techniques for infrared spectroscopy are summarized in this review article. It has also outlined the applicability of infrared spectroscopy to identify the specific biomarkers for diseases such as diabetes, acute gastritis caused by bacterial infection, cerebral palsy, and prostate cancer.

Modelling of Breath and Various Blood Volatilomic Profiles—Implications for Breath Volatile Analysis

Researchers looking for biomarkers from different sources, such as breath, urine, or blood, frequently search for specific patterns of volatile organic compounds (VOCs), often using pattern recognition or machine learning techniques. However, they are not generally aware that these patterns change depending on the source they use. Therefore, we have created a simple model to demonstrate that the distribution patterns of VOCs in fat, mixed venous blood, alveolar air, and end-tidal breath are different. Our approach follows well-established models for the description of dynamic real-time breath concentration profiles. We start with a uniform distribution of end-tidal concentrations of selected VOCs and calculate the corresponding target concentrations. For this, we only need partition coefficients, mass balance, and the assumption of an equilibrium state, which avoids the need to know the volatiles’ metabolic rates and production rates within the different compartments.

Two-dimensional Infrared Spectroscopy Reveals Better Insights of Structure and Dynamics of Protein

Proteins play an important role in biological and biochemical processes taking place in the living system. To uncover these fundamental processes of the living system, it is an absolutely necessary task to understand the structure and dynamics of the protein. Vibrational spectroscopy is an established tool to explore protein structure and dynamics. In particular, two-dimensional infrared (2DIR) spectroscopy has already proven its versatility to explore the protein structure and its ultrafast dynamics, and it has essentially unprecedented time resolutions to observe the vibrational dynamics of the protein. Providing several examples from our theoretical and experimental efforts, it is established here that two-dimensional vibrational spectroscopy provides exceptionally more information than one-dimensional vibrational spectroscopy. The structural information of the protein is encoded in the position, shape, and strength of the peak in 2DIR spectra. The time evolution of the 2DIR spectra allows for the visualisation of molecular motions.

Theory helps experiment to reveal VOCs in human breath

Volatile organic compounds (VOCs) present in human breath not only provide information about the internal chemistry of the body but can also be specific to diseases. Therefore, detection and analysis of specific VOCs can be used for medical diagnostics. However, up until today in spite of several existing VOC-based detection techniques and significant efforts, breath analysis is not a diagnostic method available for clinicians. Infrared absorption spectroscopy is a promising technique to fill this gap, with tens of identified VOCs in breath. Currently, a lack of digital spectral databases and several masking effects make difficult reliable molecular identification of observed absorption features. We demonstrate that calculations of rotational bands of vibrational spectra could serve as a basic method for molecular identification of spectral features observed in experiment. Results of comparison of several known VOCs spectra with the predictions of the theoretical model are presented.

Towards a standard operating procedure for revealing hidden volatile organic compounds in breath: the Fourier-transform IR spectroscopy case

Human breath contains a large amount of small volatile organic compounds (VOCs) and could therefore be used as a carrier of metabolic information for medical diagnostics. Still, in spite of several promising techniques that have been applied during the last decades to study breath content, there is a lack of breath-based diagnostic tools available for physicians. Among several promising techniques, infrared (IR) spectroscopy has already proved its potential for reliable detection of VOCs in the breath. However, due to the large dynamic range of molecular concentrations and overlapping absorption spectra of different VOCs, many low-absorption molecules stay hidden in spectroscopic measurements. To overcome this obstacle, we propose the Matryoshka method for removing masking effects and revealing the buried spectral structures in any bio-fluid in the gas phase. By exploiting both physical and digital removal steps, we demonstrate how the method reveals methane, acetone, aldehyde, and methyl butyrate in a real breath.

Determination of Macro- and Microelements in the Inflorescences of Banana Tree Using ICP OES: Evaluation of the Daily Recommendations of Intake for Humans

The inflorescence of Musa paradisiaca, known as “banana heart” is a structure that includes flowers and bracts of banana, commonly used as food source worldwide. The aims of this study were (1) to determine the mineral components of Musa paradisiaca and (2) to compare the obtained results with previously reported data of Recommendation Dietary Allowances (RDAs) and edible plant permissible limits set by FAO/WHO. The samples were digested using microwave-assisted equipment, while elemental contents were determined by inductively coupled plasma optical emission spectroscopy (ICP OES). Metal (Mg, Ca, Cr, Ni, Cu, Fe, and Zn) and nonmetal (S and P) contents were detected. According to RDA, the inflorescences could be excellent sources of Mg, P, Cr, Cu, Zn, and Fe for females, males, and pregnant women, all age 31–50 y, as well as children (4–8 y). Bracts are good source of Zn for male and pregnant women and good source of Fe for children. All the samples contained considerable amounts of Mg, Ca, P, Ni, Cu, Zn, and Fe, which were quite low to induce deleterious effects (UL). FAO/WHO limits for edible plants have not yet been established for S, P, Mg, and Ca, but Ni and Zn are below of those limit values. However, Cr and Cu concentrations are higher than the values established for edible plants and may pose a threat to human health. Farmers should be encouraged by government agencies, not only for sustainability of production but also to ensure the storage and trade of banana tree inflorescence.

Quantitative Analysis and Discrimination of Partially Fermented Teas from Different Origins Using Visible/Near-Infrared Spectroscopy Coupled with Chemometrics

Partially fermented tea such as oolong tea is a popular drink worldwide. Preventing fraud in partially fermented tea has become imperative to protect producers and consumers from possible economic losses. Visible/near-infrared (VIS/NIR) spectroscopy integrated with stepwise multiple linear regression (SMLR) and support vector machine (SVM) methods were used for origin discrimination of partially fermented tea from Vietnam, China, and different production areas in Taiwan using the full visible NIR wavelength range (400-2498 nm). The SMLR and SVM models achieved satisfactory results. Models using data from chemical constituents' specific wavelength ranges exhibited a high correlation with the spectra of teas, and the SMLR analyses improved discrimination of the types and origins when performing SVM analyses. The SVM models' identification accuracies regarding different production areas in Taiwan were effectively enhanced using a combination of the data within specific wavelength ranges of several constituents. The accuracy rates were 100% for the discrimination of types, origins, and production areas of tea in the calibration and prediction sets using the optimal SVM models integrated with the specific wavelength ranges of the constituents in tea. NIR could be an effective tool for rapid, nondestructive, and accurate inspection of types, origins, and production areas of teas.