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Neonatal Exhaled Breath Sampling for Infrared Spectroscopy: Biomarker Analysis
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  • Nadia Feddahi
    Nadia Feddahi
    Center for Translational and Neurobehavioural Sciences CTNBS, Department of Pediatrics I, Neonatology, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, Essen 45147, Germany
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  • Lea Hartmann
    Lea Hartmann
    Center for Translational and Neurobehavioural Sciences CTNBS, Department of Pediatrics I, Neonatology, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, Essen 45147, Germany
    More by Lea Hartmann
  • Ursula Felderhoff-Müser
    Ursula Felderhoff-Müser
    Center for Translational and Neurobehavioural Sciences CTNBS, Department of Pediatrics I, Neonatology, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, Essen 45147, Germany
    More by Ursula Felderhoff-Müser
  • Susmita Roy
    Susmita Roy
    Research Unit of the Buhl-Strohmaier Foundation for Cerebral Palsy and Pediatric Neuroorthopaedics, Department of Orthopaedics and Sports Orthopaedics, TUM School of Medicine and Health, University Hospital Rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675 Munich, Germany
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  • Renée Lampe
    Renée Lampe
    Research Unit of the Buhl-Strohmaier Foundation for Cerebral Palsy and Pediatric Neuroorthopaedics, Department of Orthopaedics and Sports Orthopaedics, TUM School of Medicine and Health, University Hospital Rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675 Munich, Germany
    Markus Würth Professorship, Technical University of Munich, Ismaninger Straße 22, 81675 Munich, Germany
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  • Kiran Sankar Maiti*
    Kiran Sankar Maiti
    TUM School of Natural Sciences, Department of Chemistry, Technical University of Munich, 85748 Garching, Germany
    Max-Planck-Institut für Quantenoptik, Hans-Kopfermann-Straße 1, 85748 Garching, Germany
    *Phone: +49 89 289 13438. Fax: +49 89 289 13416. E-mail: [email protected]
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    Orcidhttps://orcid.org/0000-0002-7337-7541
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ACS Omega

Cite this: ACS Omega 2024, 9, 28, 30625–30635
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https://doi.org/10.1021/acsomega.4c02635
Published July 2, 2024

Copyright © 2024 The Authors. Published by American Chemical Society. This publication is licensed under

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Abstract

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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.

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Introduction

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Health monitoring of preterm born, as well as term born neonates with complications such as perinatal asphyxia or sepsis, remains a major challenge for clinicians, despite recent improvements in survival rates due to advancements in obstetrics and neonatal intensive care. (1−3) In preterms, challenges arise from numerous problems that may affect their developmental progress. (4−6) In particular, clinicians face a significant challenge in the complex interplay between prenatal maternal health factors and potential immaturity complications such as bronchopulmonary dysplasia (BPD), inflammatory events (sepsis, necrotizing enterocolitis─NEC) or intraventricular hemorrhage (IVH), and socioeconomic factors. (7−9) The risk for cerebral palsy (CP) or other neurological disorders for example, inversely correlates with gestational age (GA); meaning that the earlier children are born, the higher the risk for neurological impairment. (10,11) Despite the use of sophisticated methods for monitoring health and diagnostic scores, it is almost impossible to predict the clinical or neurological outcomes of these children during their perinatal inpatient stay. For example, although, the risk of infantile CP is related to GA, usually it is diagnosed at the age of 1–2 years. (12−14) This is because children can be in a transitional phase during their development, in which it is not yet clear whether permanent disability will develop or whether the developmental delay will normalize. (15,16) Therefore, monitoring the health status of these neonates is crucial to effectively address arising problems potentially affecting their development. (17−19) In addition, it is important to make an early developmental prognosis, both to initiate supportive interventions early and to communicate this prognosis to parents. (20,21) To overcome these challenges, the ideal health monitoring approach would be noninvasive, noncontact, and radiation-free diagnostic methods to avoid unnecessary stress, risks, and side effects for the children.
In this regard, metabolites-based diagnosis certainly would be an attractive option, (22,23) since many metabolites can be collected noninvasively via, urine, faeces, exhaled breath, etc. (24,25) It is an established fact that metabolites, which are byproducts of biochemical reactions in the living cell, carry specific cellular information. (26,27) Analyzing the chemical compositions of these metabolites allows insights into the body’s internal chemistry, facilitating better monitoring of the body’s state, (22,28) as well as an indication of diseases that remain asymptomatic in their initial stages. (29−31) As bioprobe, exhaled breath stands out as a particularly promising source of metabolites for clinical diagnosis, (32) primarily due to its noninvasiveness, patient-friendly nature, and rapid processing capabilities. Since the 1970s, numerous studies have investigated breath-based metabolites in the adult population. (33) The primary reason for selecting adults as the test group is the convenience of sample collection. Currently, individuals being tested still need to exhale directly into the measurement system or a storage device. However, there remains significant debate surrounding sample collection, even for adults. (34) Certain demographics, such as infants or individuals who are immobile, weak, or in intensive care, face challenges in performing the required exhalation maneuvers for breath analysis. Recent research has made strides in addressing these challenges. In one study, breath samples were collected from 16 infants using Nalophan bags. (35) In another study, the exhaled breath of neonates was directly collected from the respiratory support system using a sampling pump. (36) Furthermore, beyond newborns, research has expanded to include the analysis of volatile organic compounds (VOCs) in the exhaled breath of pregnant sheep. This exploration holds significant promise for identifying pregnancies complicated by intra-amniotic infections. (37)
Various experimental techniques, e.g., different mass spectrometry (MS) techniques, infrared (IR) spectroscopy, electronic nose (e-nose), etc. are rapidly developing to reveal gaseous metabolites and have already demonstrated their contributions to breath research. (38,39) It is worth noting that MS techniques currently play the most significant role in breath research, identifying hundreds of VOCs with an impressive sensitivity down to 100 ppt (parts per trillion). (40) However, the complex and underdeveloped sample preparation process in MS leads to accuracy issues, which raises doubts about its reliability for medical diagnosis. (41) Furthermore, MS devices are costly and bulky in size. In contrast, e-nose devices are more cost-effective and compact. (42,43) They use an array of chemical sensors to mimic the human olfactory system. (44) However, their “black box” nature has resulted in varying outcomes across research groups. Moreover, e-nose devices are not suitable for the identification of metabolites. (45)
Compared to mass spectrometry and e-nose devices, infrared spectroscopy offers several advantages in the identification and quantification of molecular compositions from a mixture of molecules in the gas. It uses the most fundamental molecular properties, e.g., molecular vibrations, as a probe to identify the molecule through structural analysis. (46−49) Infrared light is used to stimulate molecular bonds and consequently, the absorption of light during their vibrational motion is recorded by an infrared detector. This process leads to the generation of a distinctive set of spectral features for each molecule in the acquired infrared spectra. In the realm of clinical spectroscopy, these distinct spectral features are commonly referred to as “fingerprints” of the molecule. (50,51) The precise characteristics, including the position, intensity, and morphology of these molecular fingerprints, play a crucial role in advancing metabolite-based infrared diagnostics. (52,53)
Notably, infrared spectroscopy has already demonstrated its efficacy in identifying biomarkers for various diseases in the adult population. (14,29) Here, we hypothesize that infrared spectroscopy for breath biomarker analysis can also contribute to neonatal health monitoring, provided a feasible means of collecting an adequate quantity of exhaled breath can be established. We outline a procedure for the collection of neonatal exhaled breath and the corresponding measurement techniques.

Experimental Method

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Sample Collection

Preterms or critically ill newborn infants are kept in a meticulously controlled environment, akin to a pristine clean room. The use of any equipment is strictly limited. Therefore, all spectroscopic measurements were conducted offline. The current state-of-the-art method for breath sample collection and storage for infrared diagnosis involves using a single-use Tedlar bag (Supelco Tedlar Bags, LOT#: 10311LC19C). (54) The sample collection bags are equipped with a valve through which a participant can actively blow exhaled air, just as simple as blowing a balloon. In the case of newborns, sample collection needed to be performed passively, representing the major challenge for the development of this noninvasive, noncontact, metabolites-based diagnostic tool. Further adjustments were required depending on the type of respiratory support (invasive, noninvasive CPAP) and also depending on the type of care (incubator, baby cod). The collection procedures are presented in Figure 1 using a model.

Figure 1

Figure 1. Collection procedures of exhaled breath samples from neonates are depicted with the help of a model. Passive breath sample collection for neonates under various conditions, including (a) spontaneously breathing neonate, (b) air from the incubator with neonate, (c) neonate with CPAP delivered via ”infant flow” as respiratory support, and (d) intubated neonate.

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Study Design

This prospective cohort single-center study was approved by the Ethics Committee of the Faculty of Medicine at the Technical University of Munich (Reference Number: 146/21 S-EB) and the Ethics Committee of the Medical Faculty of the University of Duisburg-Essen (Reference Number: 21-10068-BO), and conducted in accordance with the Declaration of Helsinki. All experimental protocols, as well as procedures related to patients’ data privacy and personal interests, received approval. Before collecting breath samples, the parents of the neonates were duly informed about the study and provided their written consent.
Following parental informed consent 50 preterm and 21 healthy term born at the University Hospital Essen between 01/04/2022 and 24/01/2023 with gestational age (GA) between 24+1 (the subscript stands for days) and 40+2 weeks (mean GA 32+6 weeks) and birth weight (BW) between 425 and 4270 g (mean BW 1985.6 g) were included in this study (Figure 2). The total number of samples was subdivided by GA into five subgroups. Neonates born at or beyond 37+0 weeks were categorized as “term born”. Breath samples of 21 healthy term born infants with an average GA of 39+3 weeks (born between 37+1 and 40+2 weeks) and an average BW of 3294 g (born with a BW between 2690 and 4270 g) were collected. The second group consisted of ”late preterm” neonates born between 35+0 and 36+6 weeks (n = 7, mean GA 35+2 (35+0 to 36+5)) and mean BW of 2585 g (ranging from 1700 to 3520 g). The “early preterm” group included infants born between 32+0 and 34+6 weeks (n = 12, mean GA 33+3 (32+1 to 34+5)) and mean BW of 1756 g (ranging from 1300 to 2240 g). The subsequent group was “very preterm”, comprising neonates born between 28+0 and 31+6 weeks (n = 16, mean GA 30+3 (28+0 to 31+6)) mean BW 1487 g (ranging from 745 to 2400 g). In the “extreme preterm” category we considered infants born <28+0 weeks (n = 15 mean GA of 25+3 (24+1 to 27+6), mean BW of 806 g (ranging from 425 to 1135 g).

Figure 2

Figure 2. Sample population according to the GA of neonates. A blue color bar plot illustrates the mean GA for each group, with the lowest and highest GAs noted on the bars. Similarly, the red bars depict the lowest, highest, and mean BW. The left side scale corresponds to the mean GA, while the right side scale corresponds to the mean BW.

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Neonates Breathing Spontaneously (S)

Irrespective of the GA, the majority of the neonates in the study group breathed spontaneously. For them breath sampling was performed with a 50 ml syringe (Original Perfusor Syringe 50 ml, LOT: 21E18D8004) held as near as possible between mouth and nose, without touching the neonate’s skin, and slowly aspirating the exhaled air (see Figure 1a). The collected breath sample was injected into the Tedlar bag via a needle through the intended valve. This procedure was repeated 20 times to collect about 1 Liter of sample from each neonate. An equivalent volume of ambient air was collected in a separate Tedlar bag to serve as a point of comparison (reference air) for the samples collected from spontaneous breathing.

Neonates Requiring Incubator Care

For small preterm born neonates incubator care is essential due to their immature thermoregulation system. (55) To investigate the influence of exhaled breath in the entire incubator’s air, a few samples (reference sample) were collected far from the infant’s nose (see Figure 1b). Otherwise, samples were collected close to the nose. All collections were performed using a 50 mL syringe and followed the same procedure as described above in (a).

Neonates on CPAP (Infant Flow) as Respiratory Support (CPAP)

Continuous Positive Airway Pressure (CPAP) is a method of applying positive airway pressure by continuously delivering air into the respiratory tract. (56) This technique is employed to ensure a consistent pressure level, thereby ensuring the continual patency of the airway in individuals who are naturally breathing (S). Samples were collected directly from the exhalation tube of the system by holding a 50 mL syringe near the tube opening and slowly aspirating the air (see Figure 1c). Subsequently, the sample collection procedure was followed as explained above. Collected air from the inhalation tube served as a reference sample for neonates on CPAP.

Neonates on Invasive Ventilation (Draeger Babylog VN500, IT)

Invasive ventilation involves the use of a ventilator to deliver air into the airways through an endotracheal tube, maintaining a specific pressure level. (57) In the study period, only one neonate required invasive respiratory support. The sample was collected by directly connecting the Tedlar bag over an interponate to the closed system of the respirator (see Figure 1d).
All collected samples were classified according to the GA and type of respiratory support illustrated in Figure 3. It is important to note that a single syringe was used for each neonate, to prevent sample contamination.

Figure 3

Figure 3. Classification of collected samples according to the GA of the neonates as well as their life and respiratory support. The subscript in GA indicates the days, e.g., GA = 36+6 weeks mean 36 weeks and 6 days.

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Sample Preparation

All samples collected at University Hospital Essen were stored at 4 °C for a maximum of 7 days prior to transfer to the Department of Physics, Ludwig-Maximilians University of Munich for spectroscopic analysis. Samples were transported in well-sealed polystyrene boxes with cold packs. Samples arrived within 24 h and were measured immediately upon arrival. It is important to note that the majority of samples were transferred within 2–3 days of collection, therefore, they were analyzed 2–4 days after collection. In such a short time frame, we do not anticipate any leakage or degradation of the samples. This was confirmed by a separate study involving 10 aliquoted samples from healthy adults. All samples were stored at 4 °C and analyzed up to 30 days after collection. There was no significant change in the molecular concentration of breath metabolites observed until day 20. However, a slight decrease (approximately 20% by the 30th day) in CO2 concentration was noted thereafter. Notably, there were practically no deviations observed for the other molecules analyzed, which are larger in size than CO2.
Compared to the other breath sample analysis techniques, infrared spectroscopy requires a minimal sample preparation process. The primary challenge encountered when applying infrared spectroscopy to exhaled breath is the substantial presence of water within the samples. However, a recent advancement in water suppression technique for gaseous biofluids has introduced a promising avenue for conducting infrared spectroscopic analyses on gaseous biofluids. (58) To prepare samples amenable to infrared spectroscopic analysis, a self-built water suppression system was employed. Figure 4 provides a schematic overview of the water suppression technique, coupled with the spectroscopic measurement unit. The details of the system and its working principle were reported earlier. (58) In brief, the sample preparation technique consisted of two major units, namely, (1) a sample collector and (2) a sample preparation unit. (1) The sample collector system was designed in such a way that it could accept gaseous samples as well as the headspace of liquid biofluids. Prior to sample injection into the sample collector, the entire sample path was evacuated (down to a pressure level of 10–5 mbar) using two vacuum pumps. This process effectively eliminates any residual contamination from previous measurements. Breath samples were transferred to the empty sample collector by releasing the valve. (2) The sample preparation unit was composed of essential components, including a water condenser and both heat and refrigerated circulators. The water condenser was designed as a sealed metal chamber housing a 12-m-long copper tube coiled into a spiral configuration. This copper tube served as the conduit for transferring the breath sample from the sample collector to a measurement cell. Prior to its passage through the water condenser, the chamber was meticulously cooled to a temperature of −60 °C using a refrigerated circulator. Once the water condenser reached this frigid temperature, the breath sample was allowed to flow through the spiral copper tube at a precisely controlled rate of 3 mL per second. During this transit through the cold copper tubing, a substantial amount of water vapor was effectively removed from the sample. Remarkably, an impressive water vapor reduction factor exceeding 2500 was achieved when the sample passed through the water condenser at −60 °C. Subsequently, the water-suppressed gas-phase biofluid was transferred to the multipass sample cell. Following each experimental run, the copper tube undertook a cleaning procedure by heating up the chamber to 45 °C with the heat circulator and vacuum pumps.

Figure 4

Figure 4. Diagram of the experimental scheme for gaseous biofluid analysis by infrared spectroscopy. It consists of three major parts: (1) Collection─in this part, breath or headspace of liquid biofluids is collected; (2) Preparation─a water-suppressed sample is prepared for infrared spectroscopy when gaseous biofluids are passing through the “Water Condenser”; and (3) Analysis─water suppressed gaseous sample is collected in a multipass gas cell and measured with an FTIR spectrometer.

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Spectroscopic Measurements

All the spectroscopic measurements of breath samples were performed using an FTIR spectrometer (Vertex 70, Bruker Optics GmbH, Germany). The spectrometer operated within a spectral range of 500–4000 cm–1 and utilized a 4-m optical path length along with a 2-L “White cell” (Bruker Optics GmbH, Germany) to hold gaseous samples for spectroscopic analysis. The absorption spectra of breath samples were captured by a liquid nitrogen-cooled MCT detector. For all measurements, a 0.5 cm–1 spectral resolution was used. To reduce the noise, 100 spectra were collected and averaged for each sample. The spectrometer demonstrated a sensitivity of 10 parts per billion (ppb) for VOCs within the range of moderate water absorption.

Spectroscopic Data Analysis

The absorption spectra of breath samples were analyzed by component analysis. (59,60) Initially, significant spectral features were searched from the infrared spectra of breath. Gas-phase molecular spectra were fitted with the observed spectral features in the breath sample using least-squares fitting in order to find out the best agreement. (59) Usually, gas-phase molecular spectra were collected from commercial databases (e.g., PNNL, (61) HITRAN, (62) NIST (63)) or acquiring spectra experimentally as well as theoretically by quantum chemistry calculations. (59,64)

Results and Discussions

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The primary goal of our study was to establish the reliability of sample collection from neonates from different gestational age groups. It is a well-known fact that human exhaled air volume strongly depends on body weight. (65) Therefore, a high dynamic range of exhaled air is expected from different sample groups as the body weight of the neonates largely varies. While we analyzed individually the collected exhaled breath samples of 71 neonates, for demonstration purposes, only one case from each group is presented graphically. The summary of our results is presented in Table 1.
Table 1. Number of Samples for Each Sampling Method in Which Metabolites Are Detecteda
sampling methodsmetabolites
 carbon dioxidecarbon monoxidemethanemodified
 detectedelevateddetectedelevated methane
spontaneous555555475515
incubatorCPAP15151511152
Infantflow111111
a

The elevation of absorption strength of metabolites was analyzed with respect to the corresponding reference spectra.

IR Spectra of Room Air

To validate the reliability of our exhaled breath sampling methods, we initiated a comparative study involving the analysis of infrared spectra from four distinct sources: the ambient air, exhaled breath of neonates without respiratory support (Figure 1a), samples from the exhalation tube (CPAP, invasive ventilation) (Figure 1 c and d), and air collected from incubators with neonate inside (Figure 1b). The primary challenge we encountered was assessing the variability within these four sample types. To address this, we initially concentrated on examining the ambient air. The reason behind this is obvious. Since our specific target group was neonates, we collected samples in close proximity to their nose and mouth, ensuring no physical contact and minimizing the risk of contamination. Consequently, a substantial amount of ambient air was inadvertently mixed with the breath samples. To conduct an accurate analysis of these mixed samples, it became imperative to segregate the contribution of ambient air. Therefore, acquiring a comprehensive understanding of the characteristics of ambient air became an essential step in the study.
A representative infrared spectrum of water-suppressed ambient air is depicted in Figure 5, revealing three prominent absorption peaks centered at approximately 670, 2350, and 3600 cm–1. These absorption peaks correspond to distinct vibrational modes of carbon dioxide (CO2). (62) CO2 is a prevalent component of atmospheric air, existing at a relatively high concentration of around 400 ppm (parts per million). (66) Furthermore, humans also emit endogenous CO2 when exhaling, contributing to the atmospheric CO2 content. Fortunately, separating these two sources of CO2 is a straightforward task through digital subtraction techniques. (59) However, extracting specific biochemical information in the body by CO2 is rather challenging, since a majority of biochemical processes in the human body produce CO2. While CO2 may not be highly informative for health monitoring, its significance in our study is elucidated in the subsequent section.

Figure 5

Figure 5. Infrared absorption spectra of room air. Inset is the 104 times magnification of the same spectra at around 3000 cm–1.

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The initially unremarkable spectra became significant when spectra were zoomed along the “absorbance axis.” This amplification, spanning three to four orders of magnitude, unveils numerous molecular signatures that provide a deeper insight into the body’s state. To illustrate, a three-order magnification centered around the spectral position at 3000 cm–1 exposes a distinct spectral pattern attributed to methane, comprising its well-defined P, Q, and R branches (58) (visible in the inset of Figure 5). Additionally, several other molecular signatures were detected, and their explanations were described in subsequent sections.

Identification of Breath of Neonates

The next question is whether passively collected breath samples obtained from different groups of neonates contained sufficient information for health monitoring through infrared spectroscopy. “Passively collected” means that these samples consisted of a combination of exhaled breath and ambient air.
To address this question, a comprehensive study was performed using samples from various groups. It is well-established that many biochemical reactions within cells generate CO2 as a byproduct. In general, CO2 is produced when carbohydrates and fats are metabolized. (67,68) The cardiovascular system plays a crucial role in transporting CO2 from tissues to the alveolar membrane of the lungs. Due to the concentration gradient of CO2 between the alveolar air and the blood vessels in the alveolar membrane, leading to the diffusion of CO2 into the alveolar air. Consequently, exhaled breath contains a significantly higher concentration of CO2 compared to inhaled air. The variability of these samples was assessed by measuring CO2 levels, which serve as a reliable indicator. (69) Given that endogenous CO2 significantly contributes to the composition of breath metabolites, the amount of CO2 content above the ambient (reference) CO2 level served as a practical measure of the proportion of exhaled breath in the collected sample.
In our practical analysis, we compared the strength of CO2 absorption in various sample types. Typically, the most pronounced CO2 infrared absorption peak is observed at around 2350 cm–1. Figure 6 demonstrates the zoomed-in spectra depicting the characteristics of CO2 absorption in different sample types including ambient air, air from an incubator (with an infant present), a sample from the inlet and outlet of CPAP and a sample of exhaled air collected from a baby without respiratory support.

Figure 6

Figure 6. Infrared absorption spectra of ambient air, incubator’s air (with neonate), and exhaled air of a neonate with spontaneous (S) respiration, inlet and outlet air of a CPAP system. Spectra are zoomed around the absorption spectra of carbon dioxide.

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It is noteworthy that the reference air varies depending on the respiratory support provided to neonates. In the simplest scenario, room air is considered as the reference for neonates without respiratory assistance. In Figure 6, the gray plot illustrates the reference spectra for nonrespiratory supported neonates. Incubators typically equipped with a controlled oxygen supply, result in lower CO2 levels compared to room air. To establish the reference for neonates in an incubator, we collected air samples distant from their mouths (refer to Figure 1b), represented by the green spectrum. As anticipated, the CO2 absorption strength was lower than the room air. For neonates on respiratory support, inhaled air is precisely controlled with elevated oxygen levels, and the inlet air served as the reference for these cases. This reference sample exhibits significantly lower CO2 compared to other references, as depicted by the blue line in Figure 6. These diverse reference air samples showcase distinct CO2 concentrations, forming the basis for further analysis.
Notably, samples collected near the neonate’s mouth exhibited the strongest CO2 absorption spectra. The CO2 absorption strength for this sample is 80% stronger than the corresponding reference, attributed to the neonate’s exhaled breath. To ensure the consistency of the sample collection process, we collected five consecutive samples from a single neonate, and the CO2 absorption strength remained consistent in each sample, indicating uniform and replicable collections.
The inset of Figure 6 displays the infrared spectra of the inlet and outlet air of CPAP. A more than 80% increase in CO2 levels in the outlet confirms the presence of neonate exhaled air. This affirms the capability of our sampling method and detection technique in accurately discerning neonate breath samples.
To estimate the minimum distance from mouth for effective sample collection, we conducted a dilution series with a healthy adult volunteer. An exponential drop in absorption strength with the distance was observed. Notably, when the sample was collected 10 cm distant from the nose, the CO2 absorption strength decreased by 50% compared to the collection closer to the nose without touching the skin. Here it is noted that samples were collected in the exhaled air flow direction.

Carbon Monoxide

To additionally support our investigations on collected exhaled breath from neonates, we explored the absorption spectra of carbon monoxide (CO). Typically, carbon monoxide is present in the atmosphere at an extremely low concentration, measuring less than 100 ppb. (70) This concentration varies based on factors such as population density, civilization, industrial activity, and geographical location. However, in the exhaled breath of healthy adults, a significant amount of CO exists as an endogenous metabolite produced due to oxidative stress in the lungs and inflammatory tissue injury. (71)
In the realm of infrared spectroscopy, the characteristic absorption spectrum of CO is typically located around 2170 cm–1. In human breath infrared spectra, the CO absorption feature is often obscured by the overlapping water absorption spectra. However, in our experiment, the robust water suppression techniques allowed us to clearly visualize the absorption spectra of CO. We have presented the absorption spectra of various sample types at CO absorption spectral region in Figure 7. In case of ambient air (red line), no measurable CO was observed. However, prominent spectral features of CO were observed for exhaled breath from neonates breathing spontaneously (S), intubated and invasively ventilated (IT) neonates, and neonates on noninvasive ventilation (CPAP) as respiratory support. This finding provides additional supportive evidence for the efficacy of our sampling method.

Figure 7

Figure 7. Infrared absorption spectra of ambient air along with exhaled breath from neonates with spontaneous (S) respiration, intubated (IT) and CPAP as respiratory support. The spectra are magnified around the absorption feature of carbon monoxide.

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Methane

Methane is one of the greenhouse gases present in the atmosphere. During inhalation, each individual inhales methane from ambient air, and a similar amount is expected in exhaled breath. In general, methane concentrations tend to be notably higher in a subset of the adult population, affirming its endogenous origin. (72) This increased methane concentration in exhaled breath has been attributed to the presence of methanogenic bacteria, (73) and it can vary among individuals based on factors such as ethnic background, diet, gut bacterial flora, and intestinal transit time. (74)
To the best of our knowledge, there is currently no research available on methane levels in the exhaled breath of neonates. Therefore, this study represents the inaugural investigation into methane concentrations in the exhaled breath of neonates. In Figure 8, we present infrared spectra of methane obtained from the ambient air, exhaled air of a neonate (see Figure 1a), air from the outlet of infantflow tube (see Figure 1c), and the air from the incubator with neonate (see Figure 1b). It is important to note that the methane molecules were not isolated from the sample. Instead, the absorption spectral region of methane was magnified and depicted in the figure. Notably, all of these spectra exhibit striking similarities in terms of absorption strength. To provide a more detailed view of the spectral strength, we have zoomed in on the spectral peak at 2948 cm–1, which is shown as an inset in Figure 8. It is evident that the spectral peaks from all four samples perfectly overlap, indicating the absence of endogenous methane in the exhaled breath of these two particular neonates. However, it is worth noting that a minor increase up to 20% in methane absorption strength was observed in a couple of neonates within our study group. Determining the source of this slight elevation in methane absorption spectra remains a challenge. In general, it is observed that methane concentrations can increase 2–10 times in the adult population. (75)

Figure 8

Figure 8. Infrared absorption spectra of ambient air, the sample from a neonate with CPAP respiratory support, air from an incubator, and exhaled air of a neonate with spontaneous (S) respiration. Spectra are zoomed around the absorption feature of methane.

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Although a minor variation in methane concentration is noted in 19 out of 71 neonates, it is insufficient to draw any meaningful conclusions regarding the gut bacterial flora. Instead, we observe a significant modification in the spectral characteristics of methane from a few neonates. For instance, Figure 9 displays spectra around 3000 cm–1 for exhaled breath from four individual infants. In Figure 9a, the spectra’s baseline appears largely uniform, as expected. When there is no overlap with other molecular spectra, methane spectra typically exhibit a flat baseline. However, in Figure 9b, a slight modification is detected in the P-branch of the methane spectra. A previous study documented a similar change in methane spectra. (76) Nevertheless, in the current investigation, we do not have the opportunity to further explore the underlying causes of this spectral modification.

Figure 9

Figure 9. (a–d) Infrared spectra of breath in the spectral region of methane for four different neonates. The spectral feature of methane is modified due to the presence of unknown endogenous metabolites.

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A similar modification is observed in both Figure 9c and Figure 9d, but its impact is significantly more pronounced than in Figure 9b. Interestingly, these two samples originated from twins. Regardless of the underlying reason for this spectral characteristic, both infants exhibit the same concentration of this specific metabolite. A similar spectral feature was observed in exhaled breath of 18 out of the 71 neonates. Notably, the spectral intensity of this attribute varies among individuals, suggesting that all 18 neonates possess this specific metabolite, although in varying concentrations.
Table 1 provides an overview of three metabolites discussed in this article. While we have identified many more metabolic signatures in the exhaled breath of neonates, methane, CO2, and CO are consistently present in all samples. However, the elevation of absorption strength is not uniform. In particular, no elevation of carbon monoxide was observed for a few samples, both in the case of spontaneous breathing and CPAP respiratory support. It is possible that those neonates exhaled significantly small amounts of carbon monoxide, falling below our detection limit. Another possibility is the nonuniformity in the sample collection. Despite the efforts of two skilled clinicians, the challenging health conditions of neonates may have affected the consistency of sample collection. This underscores the necessity to reassess our sample collection procedure to ensure uniformity, and we are actively working on refining the technique for this purpose. Furthermore, the analysis technique and identification of breath biomarkers can be further improved by employing GC-MS analysis in conjunction with the present FTIR technique.

Conclusions

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To the best of our knowledge, we demonstrate the first study on exhaled breath of 71 preterm and term born newborns using infrared spectroscopy. Four different methods were explored for collecting breath samples, depending on the type of respiratory support required.
Among the four sampling techniques investigated, the method involving sample collection between the nose and mouth was the simplest way of sample collection which yielded the most promising results. Exhaled breath and reference sample collections from neonates with respiratory supports seem more challenging compared to spontaneously breathing neonates. It is imperative to reassess and refine the sampling procedure.
By utilizing the infrared molecular spectral characteristics of carbon dioxide and carbon monoxide, the study demonstrated the effectiveness of the sample collection techniques in gathering exhaled breath from neonates. Although a slight increase in methane concentration was observed in the exhaled breath of 19 neonates, it is not enough to conclude its endogenous origin. However, the modification of methane spectra in 18 out of 71 neonates unambiguously manifests the exhaled breath sample collection. The exact cause of this spectral modification remains unidentified. Nevertheless, it is intriguing to note that this feature was consistently present in the case of twins, suggesting a potential shared physiological characteristic among them.
The developed breath collection method would definitely be extremely valuable for monitoring the health of newborns. Consequently, we believe this technique will empower us to identify biomarkers, with a particular focus on those associated with neurological diseases that may remain asymptomatic at a very early age.

Author Information

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  • Corresponding Author
    • Kiran Sankar Maiti - TUM School of Natural Sciences, Department of Chemistry, Technical University of Munich, 85748 Garching, Germany;  Max-Planck-Institut für Quantenoptik, Hans-Kopfermann-Straße 1, 85748 Garching, Germany;  Orcidhttps://orcid.org/0000-0002-7337-7541;  Email: [email protected]
  • Authors
    • Nadia Feddahi - Center for Translational and Neurobehavioural Sciences CTNBS, Department of Pediatrics I, Neonatology, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, Essen 45147, Germany
    • Lea Hartmann - Center for Translational and Neurobehavioural Sciences CTNBS, Department of Pediatrics I, Neonatology, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, Essen 45147, Germany
    • Ursula Felderhoff-Müser - Center for Translational and Neurobehavioural Sciences CTNBS, Department of Pediatrics I, Neonatology, University Hospital Essen, University of Duisburg-Essen, Hufelandstraße 55, Essen 45147, Germany
    • Susmita Roy - Research Unit of the Buhl-Strohmaier Foundation for Cerebral Palsy and Pediatric Neuroorthopaedics, Department of Orthopaedics and Sports Orthopaedics, TUM School of Medicine and Health, University Hospital Rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675 Munich, Germany
    • Renée Lampe - Research Unit of the Buhl-Strohmaier Foundation for Cerebral Palsy and Pediatric Neuroorthopaedics, Department of Orthopaedics and Sports Orthopaedics, TUM School of Medicine and Health, University Hospital Rechts der Isar, Technical University of Munich, Ismaninger Straße 22, 81675 Munich, Germany;  Markus Würth Professorship, Technical University of Munich, Ismaninger Straße 22, 81675 Munich, Germany
  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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R.L. acknowledges the funding from Buhl-Strohmaier and Würth Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. K.S.M. acknowledges partial financial support from DFG. The authors thank all parents for their support of this study. The authors also thank Ferenc Krausz and Mihaela Žigman for their support with experimental facilities and ideas for the improvement of the study. Frank Fleischmann is acknowledged for technical support.

References

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This article references 76 other publications.

  1. 1
    Lawn, J. E. Small babies, big risks: global estimates of prevalence and mortality for vulnerable newborns to accelerate change and improve counting. Lancet 2023, 401, 1707– 1719,  DOI: 10.1016/S0140-6736(23)00522-6
    Google Scholar
    There is no corresponding record for this reference.
  2. 2
    Gallagher, K.; Shaw, C.; Parisaei, M.; Marlow, N.; Aladangady, N. Attitudes About Extremely Preterm Birth Among Obstetric and Neonatal Health Care Professionals in England. JAMA Network Open 2022, 5, e2241802  DOI: 10.1001/jamanetworkopen.2022.41802
    Google Scholar
    There is no corresponding record for this reference.
  3. 3
    Behrman, R. E., Butler, A. S., Eds. Preterm Birth; National Academies Press: Washington, D.C., 2007.
    Google Scholar
    There is no corresponding record for this reference.
  4. 4
    Zhao, Y.; Liu, G.; Liang, L.; Yu, Z. Relationship of plasma MBP and 8-oxo-dG with brain damage in preterm. Open Medicine 2022, 17, 1674– 1681,  DOI: 10.1515/med-2022-0566
    Google Scholar
    There is no corresponding record for this reference.
  5. 5
    Iroh Tam, P.-Y.; Bendel, C. M Diagnostics for neonatal sepsis: current approaches and future directions. Pediatr. Res. 2017, 82, 574– 583,  DOI: 10.1038/pr.2017.134
    Google Scholar
    There is no corresponding record for this reference.
  6. 6
    Ashorn, P. Small vulnerable newborns-big potential for impact. Lancet 2023, 401, 1692– 1706,  DOI: 10.1016/S0140-6736(23)00354-9
    Google Scholar
    There is no corresponding record for this reference.
  7. 7
    Linsell, L.; Malouf, R.; Morris, J.; Kurinczuk, J. J.; Marlow, N. Risk Factor Models for Neurodevelopmental Outcomes in Children Born Very Preterm or With Very Low Birth Weight: A Systematic Review of Methodology and Reporting. American Journal of Epidemiology 2017, 185, 601– 612,  DOI: 10.1093/aje/kww135
    Google Scholar
    There is no corresponding record for this reference.
  8. 8
    Tataranno, M. L.; Vijlbrief, D. C.; Dudink, J.; Benders, M. J. N. L. Precision Medicine in Neonates: A Tailored Approach to Neonatal Brain Injury. Front. Pediatr. 2021, 9 DOI: 10.3389/fped.2021.634092 .
    Google Scholar
    There is no corresponding record for this reference.
  9. 9
    Felderhoff-Müser, U.; Hüning, B. Biomarker und Neuromonitoring zur Entwicklungsprognose nach perinataler Hirnschädigung. Monatsschrift Kinderheilkunde 2022, 170, 688– 703,  DOI: 10.1007/s00112-022-01542-4
    Google Scholar
    There is no corresponding record for this reference.
  10. 10
    Marlow, N.; Wolke, D.; Bracewell, M. A.; Samara, M. Neurologic and Developmental Disability at Six Years of Age after Extremely Preterm Birth. New England Journal of Medicine 2005, 352, 9– 19,  DOI: 10.1056/NEJMoa041367
    Google Scholar
    There is no corresponding record for this reference.
  11. 11
    Spittle, A. J.; Orton, J. Cerebral palsy and developmental coordination disorder in children born preterm. Seminars in Fetal and Neonatal Medicine 2014, 19, 84– 89,  DOI: 10.1016/j.siny.2013.11.005
    Google Scholar
    There is no corresponding record for this reference.

    Long-term outcome for the tiniest or most immature babies.

  12. 12
    Ellenberg, J. H.; Nelson, K. B. Early Recognition of Infants at High Risk for Cerebral Palsy: Examination at Age Four Months. Developmental Medicine & Child Neurology 1981, 23, 705– 716,  DOI: 10.1111/j.1469-8749.1981.tb02059.x
    Google Scholar
    There is no corresponding record for this reference.
  13. 13
    Herskind, A.; Greisen, G.; Nielsen, J. B. Early identification and intervention in cerebral palsy. Developmental Medicine & Child Neurology 2015, 57, 29– 36,  DOI: 10.1111/dmcn.12531
    Google Scholar
    There is no corresponding record for this reference.
  14. 14
    Maiti, K. S.; Roy, S.; Lampe, R.; Apolonski, A. Breath indeed carries significant information about a disease. Potential biomarkers of cerebral palsy. J. Biophotonics 2020, 13, e202000125  DOI: 10.1002/jbio.202000125
    Google Scholar
    There is no corresponding record for this reference.
  15. 15
    McIntyre, S.; Morgan, C.; Walker, K.; Novak, I. Cerebral Palsy─Don’t Delay. Developmental Disabilities Research Reviews 2011, 17, 114– 129,  DOI: 10.1002/ddrr.1106
    Google Scholar
    There is no corresponding record for this reference.
  16. 16
    te Velde, A.; Morgan, C.; Novak, I.; Tantsis, E.; Badawi, N. Badawi Early Diagnosis and Classification of Cerebral Palsy: An Historical Perspective and Barriers to an Early Diagnosis. J. Clin. Med. 2019, 8, 1599,  DOI: 10.3390/jcm8101599
    Google Scholar
    There is no corresponding record for this reference.
  17. 17
    Meem, M.; Modak, J. K.; Mortuza, R.; Morshed, M.; Islam, M. S.; Saha, S. K. Biomarkers for diagnosis of neonatal infections: A systematic analysis of their potential as a point-of-care diagnostics. J. Glob. Health 2011, 1 (2), 201– 209
    Google Scholar
    There is no corresponding record for this reference.
  18. 18
    Celik, I. H.; Hanna, M.; Canpolat, F. E.; Pammi, M. Diagnosis of neonatal sepsis: the past, present and future. Pediatr. Res. 2022, 91 (2), 337– 350,  DOI: 10.1038/s41390-021-01696-z
    Google Scholar
    18
    Diagnosis of neonatal sepsis: the past, present and future
    Celik Istemi Han; Canpolat Fuat Emre; Celik Istemi Han; Hanna Morcos; Mohan Pammi; Canpolat Fuat Emre
    Pediatric research (2022), 91 (2), 337-350 ISSN:.
    Sepsis remains a significant cause of neonatal mortality and morbidity, especially in low- and middle-income countries. Neonatal sepsis presents with nonspecific signs and symptoms that necessitate tests to confirm the diagnosis. Early and accurate diagnosis of infection will improve clinical outcomes and decrease the overuse of antibiotics. Current diagnostic methods rely on conventional culture methods, which is time-consuming, and may delay critical therapeutic decisions. Nonculture-based techniques including molecular methods and mass spectrometry may overcome some of the limitations seen with culture-based techniques. Biomarkers including hematological indices, cell adhesion molecules, interleukins, and acute-phase reactants have been used for the diagnosis of neonatal sepsis. In this review, we examine past and current microbiological techniques, hematological indices, and inflammatory biomarkers that may aid sepsis diagnosis. The search for an ideal biomarker that has adequate diagnostic accuracy early in sepsis is still ongoing. We discuss promising strategies for the future that are being developed and tested that may help us diagnose sepsis early and improve clinical outcomes. IMPACT: Reviews the clinical relevance of currently available diagnostic tests for sepsis. Summarizes the diagnostic accuracy of novel biomarkers for neonatal sepsis. Outlines future strategies including the use of omics technology, personalized medicine, and point of care tests.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB2cjotFKiuw%253D%253D&md5=567b7bb0119214734e15907dfa115bde
  19. 19
    Mahwasane, T.; Maputle, M. S.; Simane-Netshisaulu, K. G.; Malwela, T. Provision of Care to Preterm Infants at Resource Limited Health Facilities of Mopani District, South Africa. Annals of Global Health 2020, 86, 10,  DOI: 10.5334/aogh.2555
    Google Scholar
    There is no corresponding record for this reference.
  20. 20
    Boland, R. A.; Davis, P. G.; Dawson, J. A.; Doyle, L. W. What are we telling the parents of extremely preterm babies?. Australian and New Zealand Journal of Obstetrics and Gynaecology 2016, 56, 274– 281,  DOI: 10.1111/ajo.12448
    Google Scholar
    There is no corresponding record for this reference.
  21. 21
    Patel, R. M.; Rysavy, M. A.; Bell, E. F.; Tyson, J. E. Survival of Infants Born at Periviable Gestational Ages. Clinics in Perinatology 2017, 44, 287– 303,  DOI: 10.1016/j.clp.2017.01.009
    Google Scholar
    There is no corresponding record for this reference.
  22. 22
    Maiti, K. S.; Lewton, M.; Fill, E.; Apolonski, A. Human beings as islands of stability: Monitoring body states using breath profiles. Sci. Rep. 2019, 9, 16167,  DOI: 10.1038/s41598-019-51417-0
    Google Scholar
    There is no corresponding record for this reference.
  23. 23
    Qiu, S.; Cai, Y.; Yao, H.; Lin, C.; Xie, Y.; Tang, S.; Zhang, A.; Small molecule metabolites: discovery of biomarkers and therapeutic targets. Sig. Transduct. Target Ther. 2023, 8 DOI: 10.1038/s41392-023-01399-3 .
    Google Scholar
    There is no corresponding record for this reference.
  24. 24
    Shirasu, M.; Touhara, K. The scent of disease: volatile organic compounds of the human body related to disease and disorder. Journal of Biochemistry 2011, 150, 257,  DOI: 10.1093/jb/mvr090
    Google Scholar
    24
    The scent of disease: volatile organic compounds of the human body related to disease and disorder
    Shirasu, Mika; Touhara, Kazushige
    Journal of Biochemistry (2011), 150 (3), 257-266CODEN: JOBIAO; ISSN:0021-924X. (Oxford University Press)
    A review. Hundreds of volatile org. compds. (VOCs) are emitted from the human body, and the components of VOCs usually reflect the metabolic condition of an individual. Therefore, contracting an infectious or metabolic disease often results in a change in body odor. Recent progresses in anal. techniques allow rapid analyses of VOCs derived from breath, blood, skin and urine. Disease-specific VOCs can be used as diagnostic olfactory biomarkers of infectious diseases, metabolic diseases, genetic disorders and other kinds of diseases. Elucidation of pathophysiol. mechanisms underlying prodn. of disease-specific VOCs may provide novel insights into therapeutic approaches for treatments for various diseases. This review summarizes the current knowledge on chem. and clin. aspects of body-derived VOCs, and provides a brief outlook at the future of olfactory diagnosis.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3MXhtFShtbrK&md5=b81e99e5ccc77171c2ed0e07ddbfb488
  25. 25
    Drabińska, N.; Flynn, C.; Ratcliffe, N.; Belluomo, I. A literature survey of all volatiles from healthy human breath and bodily fluids: the human volatilome. Journal of Breath Research 2021, 15, 034001,  DOI: 10.1088/1752-7163/abf1d0
    Google Scholar
    There is no corresponding record for this reference.
  26. 26
    Metzler, D. E. Biochemistry: The Chemical Reactions of Living Cells; Academic Press: New York, 2003.
    Google Scholar
    There is no corresponding record for this reference.
  27. 27
    Ahern, K. Biochemistry and Molecular Biology: How Life Works; Teaching Company, LLC: Chantilly, VA, 2019.
    Google Scholar
    There is no corresponding record for this reference.
  28. 28
    Huber, M.; Kepesidis, K. V.; Voronina, L.; Bozic, M.; Trubetskov, M.; Harbeck, N.; Krausz, F.; Zigman, M. Stability of person-specific blood-based infrared molecular fingerprints opens up prospects for health monitoring. Nat. Commun. 2021, 12, 1511,  DOI: 10.1038/s41467-021-21668-5
    Google Scholar
    28
    Stability of person-specific blood-based infrared molecular fingerprints opens up prospects for health monitoring
    Huber, Marinus; Kepesidis, Kosmas V.; Voronina, Liudmila; Bozic, Masa; Trubetskov, Michael; Harbeck, Nadia; Krausz, Ferenc; Zigman, Mihaela
    Nature Communications (2021), 12 (1), 1511CODEN: NCAOBW; ISSN:2041-1723. (Nature Research)
    Health state transitions are reflected in characteristic changes in the mol. compn. of biofluids. Detecting these changes in parallel, across a broad spectrum of mol. species, could contribute to the detection of abnormal physiologies. Fingerprinting of biofluids by IR vibrational spectroscopy offers that capacity. Whether its potential for health monitoring can indeed be exploited critically depends on how stable IR mol. fingerprints (IMFs) of individuals prove to be over time. Here we report a proof-of-concept study that addresses this question. Using Fourier-transform IR spectroscopy, we have fingerprinted blood serum and plasma samples from 31 healthy, non-symptomatic individuals, who were sampled up to 13 times over a period of 7 wk and again after 6 mo. The measurements were performed directly on liq. serum and plasma samples, yielding a time- and cost-effective workflow and a high degree of reproducibility. The resulting IMFs were found to be highly stable over clin. relevant time scales. Single measurements yielded a multiplicity of person-specific spectral markers, allowing individual mol. phenotypes to be detected and followed over time. This previously unknown temporal stability of individual biochem. fingerprints forms the basis for future applications of blood-based IR spectral fingerprinting as a multiomics-based mode of health monitoring.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXmt1alsLs%253D&md5=ea338a6ba4107472f52d394bbdf33185
  29. 29
    Maiti, K. S.; Fill, E.; Strittmatter, F.; Volz, Y.; Sroka, R.; Apolonski, A. Towards reliable diagnostics of prostate cancer via breath. Sci. Rep. 2021, 11, 18381,  DOI: 10.1038/s41598-021-96845-z
    Google Scholar
    There is no corresponding record for this reference.
  30. 30
    Maiti, K. S.; Fill, E.; Strittmatter, F.; Volz, Y.; Sroka, R.; Apolonski, A. Standard operating procedure to reveal prostate cancer specific volatile organic molecules by infrared spectroscopy. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2024, 304, 123266,  DOI: 10.1016/j.saa.2023.123266
    Google Scholar
    There is no corresponding record for this reference.
  31. 31
    Gowda, G. N.; Zhang, S.; Gu, H.; Asiago, V.; Shanaiah, N.; Raftery, D. Metabolomics-based methods for early disease diagnostics. Expert Review of Molecular Diagnostics 2008, 8, 617– 633,  DOI: 10.1586/14737159.8.5.617
    Google Scholar
    31
    Metabolomics-based methods for early disease diagnostics
    Gowda, Ga nagana; Zhang, Shucha; Gu, Haiwei; Asiago, Vincent; Shanaiah, Narasimhamurthy; Raftery, Daniel
    Expert Review of Molecular Diagnostics (2008), 8 (5), 617-633CODEN: ERMDCW; ISSN:1473-7159. (Expert Reviews Ltd.)
    A review. The emerging field of metabolomics, in which a large no. of small-mol. metabolites from body fluids or tissues are detected quant. in a single step, promises immense potential for early diagnosis, therapy monitoring and for understanding the pathogenesis of many diseases. Metabolomics methods are mostly focused on the information-rich anal. techniques of NMR spectroscopy and mass spectrometry (MS). Anal. of the data from these high-resoln. methods using advanced chemometric approaches provides a powerful platform for translational and clin. research and diagnostic applications. In this review, the current trends and recent advances in NMR- and MS-based metabolomics are described with a focus on the development of advanced NMR and MS methods, improved multivariate statistical data anal. and recent applications in the area of cancer, diabetes, inborn errors of metab. and cardiovascular diseases.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1cXhtFSms7jP&md5=cf77c8f0f22defc10c0f0943150bcdb4
  32. 32
    Beauchamp, J. D.; Davis, C.; Pleil, J. D. Breathborne Biomarkers and the Human Volatilome; Elsevier: New Amsterdam, 2020.
    Google Scholar
    There is no corresponding record for this reference.
  33. 33
    Pauling, L.; Robinson, A. B.; Teranishi, R.; Cary, P. Quantitative Analysis of Urine Vapor and Breath by Gas-Liquid Partition Chromatography. Proc. Natl. Acad. Sci. U. S. A. 1971, 68, 2374– 2376,  DOI: 10.1073/pnas.68.10.2374
    Google Scholar
    33
    Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography
    Pauling, Linus; Robinson, Arthur B.; Teranishi, Roy; Cary, Paul
    Proceedings of the National Academy of Sciences of the United States of America (1971), 68 (10), 2374-6CODEN: PNASA6; ISSN:0027-8424.
    When a human being is placed for several days on a completely define diet, consisting almost entirely of small mols. that are absorbed from the stomach into the blood, intestinal flora disappear because of lack of nutrition. By this technique, the compn. of body fluids can be made const. (std. deviation about 10%) after a few days, permitting significant quant. analyses to be performed. A method of temp.-programmed gas chromatog. was developed for this purpose. It permits the quant. detn. of about 250 substances in a sample of breath, and of about 280 substances in a sample of urine vapor. The technique should be useful in the application of the principles of orthomol. medicine.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE3MXlsVygsLc%253D&md5=f6a160ff50711caad4e11e59ebccdc8c
  34. 34
    Sukul, P.; Schubert, J. K.; Zanaty, K.; Trefz, P.; Sinha, A.; Kamysek, S.; Miekisch, W.; Exhaled breath compositions under varying respiratory rhythms reflects ventilatory variations: translating breathomics towards respiratory medicine. Sci. Rep. 2020, 10 DOI: 10.1038/s41598-020-70993-0 .
    Google Scholar
    There is no corresponding record for this reference.
  35. 35
    Decrue, F.; Singh, K. D.; Gisler, A.; Awchi, M. Combination of Exhaled Breath Analysis with Parallel Lung Function and FeNO Measurements in Infants. Anal. Chem. 2021, 93, 15579– 15583,  DOI: 10.1021/acs.analchem.1c02036
    Google Scholar
    There is no corresponding record for this reference.
  36. 36
    Romijn, M.; van Kaam, A. H.; Fenn, D.; Bos, L. D. Exhaled Volatile Organic Compounds for Early Prediction of Bronchopulmonary Dysplasia in Infants Born Preterm. Journal of Pediatrics 2023, 257, 113368,  DOI: 10.1016/j.jpeds.2023.02.014
    Google Scholar
    There is no corresponding record for this reference.
  37. 37
    Ophelders, D. R. M. G.; Boots, A. W.; Hütten, M. C.; Al-Nasiry, S.; Jellema, R. K.; Spiller, O. B.; van Schooten, F.-J.; Smolinska, A.; Wolfs, T. G. A. M. Screening of Chorioamnionitis Using Volatile Organic Compound Detection in Exhaled Breath: A Pre-clinical Proof of Concept Study. Front. Pediatr. 2021, 9, 488,  DOI: 10.3389/fped.2021.617906
    Google Scholar
    There is no corresponding record for this reference.
  38. 38
    Maiti, K. S. Non-Invasive Disease Specific Biomarker Detection Using Infrared Spectroscopy: A Review. Molecules 2023, 28, 2320,  DOI: 10.3390/molecules28052320
    Google Scholar
    There is no corresponding record for this reference.
  39. 39
    Pham, Y. L.; Beauchamp, J. Breath Biomarkers in Diagnostic Applications. Molecules 2021, 26, 5514,  DOI: 10.3390/molecules26185514
    Google Scholar
    There is no corresponding record for this reference.
  40. 40
    Li, C.; Chu, S.; Tan, S.; Yin, X.; Jiang, Y.; Dai, X.; Gong, X.; Fang, X.; Tian, D.; Towards Higher Sensitivity of Mass Spectrometry: A Perspective From the Mass Analyzers. Front. Chem. 2021, 9 DOI: 10.3389/fchem.2021.813359 .
    Google Scholar
    There is no corresponding record for this reference.
  41. 41
    Hanna, G. B.; Boshier, P. R.; Markar, S. R.; Romano, A. Accuracy and Methodologic Challenges of Volatile Organic Compound–Based Exhaled Breath Tests for Cancer Diagnosis. JAMA Oncology 2019, 5, e182815  DOI: 10.1001/jamaoncol.2018.2815
    Google Scholar
    There is no corresponding record for this reference.
  42. 42
    Karakaya, D.; Ulucan, O.; Turkan, M. Electronic Nose and Its Applications: A Survey. Int. J. Autom. Comput. 2020, 17, 179– 209,  DOI: 10.1007/s11633-019-1212-9
    Google Scholar
    There is no corresponding record for this reference.
  43. 43
    Ye, Z.; Liu, Y.; Li, Q. Recent Progress in Smart Electronic Nose Technologies Enabled with Machine Learning Methods. Sensors 2021, 21, 7620,  DOI: 10.3390/s21227620
    Google Scholar
    There is no corresponding record for this reference.
  44. 44
    Kwon, O. S.; Song, H. S.; Park, S. J.; Lee, S. H.; An, J. H. An Ultrasensitive, Selective, Multiplexed Superbioelectronic Nose That Mimics the Human Sense of Smell. Nano Lett. 2015, 15, 6559– 6567,  DOI: 10.1021/acs.nanolett.5b02286
    Google Scholar
    44
    An Ultrasensitive, Selective, Multiplexed Superbioelectronic Nose That Mimics the Human Sense of Smell
    Kwon, Oh Seok; Song, Hyun Seok; Park, Seon Joo; Lee, Seung Hwan; An, Ji Hyun; Park, Jin Wook; Yang, Heehong; Yoon, Hyeonseok; Bae, Joonwon; Park, Tai Hyun; Jang, Jyongsik
    Nano Letters (2015), 15 (10), 6559-6567CODEN: NALEFD; ISSN:1530-6984. (American Chemical Society)
    Human sensory-mimicking systems, such as electronic brains, tongues, skin, and ears, have been promoted for use in improving social welfare. However, no significant achievements have been made in mimicking the human nose due to the complexity of olfactory sensory neurons. Combinational coding of human olfactory receptors (hORs) is essential for odorant discrimination in mixts., and the development of hOR-combined multiplexed systems has progressed slowly. Here, the authors report the first demonstration of an artificial multiplexed superbioelectronic nose (MSB-nose) that mimics the human olfactory sensory system, leading to high-performance odorant discriminatory ability in mixts. Specifically, portable MSB-noses were constructed using highly uniform graphene micropatterns (GMs) that were conjugated with two different hORs, which were employed as transducers in a liq.-ion gated field-effect transistor (FET). Field-induced signals from the MSB-nose were monitored and provided high sensitivity and selectivity toward target odorants (min. detectable level: 0.1 fM). More importantly, the potential of the MSB-nose as a tool to encode hOR combinations was demonstrated using principal component anal.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2MXhsVWms7nM&md5=a6396d41dd9721285c8d386db3f0dc71
  45. 45
    Di Natale, C.; Paolesse, R.; Martinelli, E.; Capuano, R. Solid-state gas sensors for breath analysis: A review. Anal. Chim. Acta 2014, 824, 1– 17,  DOI: 10.1016/j.aca.2014.03.014
    Google Scholar
    45
    Solid-state gas sensors for breath analysis: A review
    Di Natale, Corrado; Paolesse, Roberto; Martinelli, Eugenio; Capuano, Rosamaria
    Analytica Chimica Acta (2014), 824 (), 1-17CODEN: ACACAM; ISSN:0003-2670. (Elsevier B.V.)
    A review. The anal. of volatile compds. is an efficient method to appraise information about the chem. compn. of liqs. and solids. This principle is applied to several practical applications, such as food anal. where many important features (e.g. freshness) can be directly inferred from the anal. of volatile compds. The same approach can also be applied to a human body where the volatile compds., collected from the skin, the breath or in the headspace of fluids, might contain information that could be used to diagnose several kinds of diseases. In particular, breath is widely studied and many diseases can be potentially detected from breath anal.The most fascinating property of breath anal. is the non-invasiveness of the sample collection. Solid-state sensors are considered the natural complement to breath anal., matching the non-invasiveness with typical sensor features such as low-cost, easiness of use, portability, and the integration with the information networks. Sensors based breath anal. is then expected to dramatically extend the diagnostic capabilities enabling the screening of large populations for the early diagnosis of pathologies.In the last years there has been an increased attention to the development of sensors specifically aimed to this purpose. These investigations involve both specific sensors designed to detect individual compds. and non-specific sensors, operated in array configurations, aimed at clustering subjects according to their health conditions. In this paper, the recent significant applications of these sensors to breath anal. are reviewed and discussed.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXlt1Sgt7c%253D&md5=3537987fc5dfd5f2bd6f2ab3fc7cbd25
  46. 46
    Wilson, E.; Decius, J.; Cross, P. Molecular Vibrations: The Theory of Infrared and Raman Vibrational Spectra. Dover Books on Chemistry Series; Dover Publications: New York, 1980.
    Google Scholar
    There is no corresponding record for this reference.
  47. 47
    Maiti, K. S. Vibrational spectroscopy of Methyl benzoate. Phys. Chem. Chem. Phys. 2015, 17, 19735– 19744,  DOI: 10.1039/C5CP02281A
    Google Scholar
    There is no corresponding record for this reference.
  48. 48
    Roy, S.; Maiti, K. S. Structural sensitivity of CH vibrational band in methyl benzoate. Spectrochim. Acta Mol. Biomol. Spectrosc. 2018, 196, 289– 294,  DOI: 10.1016/j.saa.2018.02.031
    Google Scholar
    There is no corresponding record for this reference.
  49. 49
    Maiti, K. S. Ultrafast vibrational coupling between C–H and C = O band of cyclic amide 2-Pyrrolidinone revealed by 2DIR spectroscopy. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2020, 228, 117749,  DOI: 10.1016/j.saa.2019.117749
    Google Scholar
    There is no corresponding record for this reference.
  50. 50
    Buchan, E.; Kelleher, L.; Clancy, M.; Stanley Rickard, J. J.; Oppenheimer, P. G. Spectroscopic molecular-fingerprint profiling of saliva. Anal. Chim. Acta 2021, 1185, 339074,  DOI: 10.1016/j.aca.2021.339074
    Google Scholar
    50
    Spectroscopic molecular-fingerprint profiling of saliva
    Buchan, Emma; Kelleher, Liam; Clancy, Michael; Stanley Rickard, Jonathan James; Oppenheimer, Pola Goldberg
    Analytica Chimica Acta (2021), 1185 (), 339074CODEN: ACACAM; ISSN:0003-2670. (Elsevier B.V.)
    Saliva anal. has been gaining interest as a potential non-invasive source of disease indicative biomarkers due to being a complex biofluid correlating with blood-based constituents on a mol. level. For saliva to cement its usage for anal. applications, it is paramount to gain underpinning mol. knowledge and establish a 'baseline' of the salivary compn. in healthy individuals as well as characterize how these factors are impacting its performance as potential anal. biofluid. Here, we have systematically studied the mol. spectral fingerprint of saliva, including the changes assocd. with gender, age, and time. Via hybrid artificial neural network algorithms and Raman spectroscopy, we have developed a non-destructive mol. profiling approach enabling the assessment of salivary spectral changes yielding the detn. of gender and age of the biofluid source. Our classification algorithm successfully identified the gender and age from saliva with high classification accuracy. Discernible spectral mol. 'barcodes' were subsequently constructed for each class and found to primarily stem from amino acid, protein, and lipid changes in saliva. This unique combination of Raman spectroscopy and advanced machine learning techniques lays the platform for a variety of applications in forensics and biosensing.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXitFant7rF&md5=0dfe105cec6afa4f3e29dc910f3435b7
  51. 51
    Maiti, K. S. Two-dimensional Infrared Spectroscopy Reveals Better Insights of Structure and Dynamics of Protein. Molecules 2021, 26, 6893,  DOI: 10.3390/molecules26226893
    Google Scholar
    There is no corresponding record for this reference.
  52. 52
    Takamura, A.; Watanabe, K.; Akutsu, T.; Ozawa, T. Soft and Robust Identification of Body Fluid Using Fourier Transform Infrared Spectroscopy and Chemometric Strategies for Forensic Analysis. Sci. Rep. 2018, 8, 8459,  DOI: 10.1038/s41598-018-26873-9
    Google Scholar
    52
    Soft and Robust Identification of Body Fluid Using Fourier Transform Infrared Spectroscopy and Chemometric Strategies for Forensic Analysis
    Takamura Ayari; Watanabe Ken; Akutsu Tomoko; Takamura Ayari; Ozawa Takeaki
    Scientific reports (2018), 8 (1), 8459 ISSN:.
    Body fluid (BF) identification is a critical part of a criminal investigation because of its ability to suggest how the crime was committed and to provide reliable origins of DNA. In contrast to current methods using serological and biochemical techniques, vibrational spectroscopic approaches provide alternative advantages for forensic BF identification, such as non-destructivity and versatility for various BF types and analytical interests. However, unexplored issues remain for its practical application to forensics; for example, a specific BF needs to be discriminated from all other suspicious materials as well as other BFs, and the method should be applicable even to aged BF samples. Herein, we describe an innovative modeling method for discriminating the ATR FT-IR spectra of various BFs, including peripheral blood, saliva, semen, urine and sweat, to meet the practical demands described above. Spectra from unexpected non-BF samples were efficiently excluded as outliers by adopting the Q-statistics technique. The robustness of the models against aged BFs was significantly improved by using the discrimination scheme of a dichotomous classification tree with hierarchical clustering. The present study advances the use of vibrational spectroscopy and a chemometric strategy for forensic BF identification.
    >> More from SciFinder ®
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  53. 53
    Apolonski, A.; Roy, S.; Lampe, R.; Sankar Maiti, K. Molecular identification of bio-fluids in gas phase using infrared spectroscopy. Appl. Opt. 2020, 59, E36– E41,  DOI: 10.1364/AO.388362
    Google Scholar
    There is no corresponding record for this reference.
  54. 54
    Mochalski, P.; King, J.; Unterkofler, K.; Amann, A. Stability of selected volatile breath constituents in Tedlar, Kynar and Flexfilm sampling bags. Analyst 2013, 138, 1405– 1418,  DOI: 10.1039/c2an36193k
    Google Scholar
    There is no corresponding record for this reference.
  55. 55
    Baker, J. The Machine in the Nursery: Incubator Technology and the Origins of Newborn Intensive Care; Johns Hopkins Introductory Studies in the History Series; Johns Hopkins University Press: Baltimore, MD, 1996.
    Google Scholar
    There is no corresponding record for this reference.
  56. 56
    Kidman, A. M.; Manley, B. J.; Boland, R. A.; Malhotra, A. Higher versus lower nasal continuous positive airway pressure for extubation of extremely preterm infants in Australia (ÉCLAT): a multicentre, randomised, superiority trial. Lancet Child & Adolescent Health 2023, 7, 844– 851,  DOI: 10.1016/S2352-4642(23)00235-3
    Google Scholar
    There is no corresponding record for this reference.
  57. 57
    Rocha, G.; Soares, P.; Gonçalves, A.; Silva, A. I. Respiratory Care for the Ventilated Neonate. Canadian Respiratory Journal 2018, 2018, 1– 12,  DOI: 10.1155/2018/7472964
    Google Scholar
    There is no corresponding record for this reference.
  58. 58
    Maiti, K. S.; Lewton, M.; Fill, E.; Apolonski, A. Sensitive spectroscopic breath analysis by water condensation. Journal of Breath Research 2018, 12, 046003,  DOI: 10.1088/1752-7163/aad207
    Google Scholar
    There is no corresponding record for this reference.
  59. 59
    Apolonski, A.; Maiti, K. S. Towards a standard operating procedure for revealing hidden volatile organic compounds in breath: the Fourier-transform IR spectroscopy case. Appl. Opt. 2021, 60, 4217– 4224,  DOI: 10.1364/AO.421994
    Google Scholar
    There is no corresponding record for this reference.
  60. 60
    Roy, S.; Maiti, K. S. Baseline correction for the infrared spectra of exhaled breath. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2024, 318, 124473,  DOI: 10.1016/j.saa.2024.124473
    Google Scholar
    There is no corresponding record for this reference.
  61. 61
    Johnson, T. J.; Sams, R. L.; Sharpe, S. W. The PNNL quantitative infrared database for gas-phase sensing: a spectral library for environmental, hazmat, and public safety standoff detection. Chemical and Biological Point Sensors for Homeland Defense 2004, 159– 167,  DOI: 10.1117/12.515604
    Google Scholar
    There is no corresponding record for this reference.
  62. 62
    Gordon, I.E.; Rothman, L.S.; Hill, C.; Kochanov, R.V.; Tan, Y.; Bernath, P.F.; Birk, M.; Boudon, V.; Campargue, A.; Chance, K.V.; Drouin, B.J.; Flaud, J.-M.; Gamache, R.R.; Hodges, J.T.; Jacquemart, D.; Perevalov, V.I.; Perrin, A.; Shine, K.P.; Smith, M.-A.H.; Tennyson, J.; Toon, G.C.; Tran, H.; Tyuterev, V.G.; Barbe, A.; Csaszar, A.G.; Devi, V.M.; Furtenbacher, T.; Harrison, J.J.; Hartmann, J.-M.; Jolly, A.; Johnson, T.J.; Karman, T.; Kleiner, I.; Kyuberis, A.A.; Loos, J.; Lyulin, O.M.; Massie, S.T.; Mikhailenko, S.N.; Moazzen-Ahmadi, N.; Muller, H.S.P.; Naumenko, O.V.; Nikitin, A.V.; Polyansky, O.L.; Rey, M.; Rotger, M.; Sharpe, S.W.; Sung, K.; Starikova, E.; Tashkun, S.A.; Auwera, J. V.; Wagner, G.; Wilzewski, J.; Wcisło, P.; Yu, S.; Zak, E.J. The HITRAN2016 molecular spectroscopic database. J. Quant. Spectrosc. Radiat. Transfer 2017, 203, 3– 69,  DOI: 10.1016/j.jqsrt.2017.06.038
    Google Scholar
    62
    The HITRAN2016 molecular spectroscopic database
    Gordon, I. E.; Rothman, L. S.; Hill, C.; Kochanov, R. V.; Tan, Y.; Bernath, P. F.; Birk, M.; Boudon, V.; Campargue, A.; Chance, K. V.; Drouin, B. J.; Flaud, J.-M.; Gamache, R. R.; Hodges, J. T.; Jacquemart, D.; Perevalov, V. I.; Perrin, A.; Shine, K. P.; Smith, M.-A. H.; Tennyson, J.; Toon, G. C.; Tran, H.; Tyuterev, V. G.; Barbe, A.; Csaszar, A. G.; Devi, V. M.; Furtenbacher, T.; Harrison, J. J.; Hartmann, J.-M.; Jolly, A.; Johnson, T. J.; Karman, T.; Kleiner, I.; Kyuberis, A. A.; Loos, J.; Lyulin, O. M.; Massie, S. T.; Mikhailenko, S. N.; Moazzen-Ahmadi, N.; Muller, H. S. P.; Naumenko, O. V.; Nikitin, A. V.; Polyansky, O. L.; Rey, M.; Rotger, M.; Sharpe, S. W.; Sung, K.; Starikova, E.; Tashkun, S. A.; Vander Auwera, J.; Wagner, G.; Wilzewski, J.; Wcislo, P.; Yu, S.; Zak, E. J.
    Journal of Quantitative Spectroscopy & Radiative Transfer (2017), 203 (), 3-69CODEN: JQSRAE; ISSN:0022-4073. (Elsevier Ltd.)
    This paper describes the contents of the 2016 edition of the HITRAN mol. spectroscopic compilation. The new edition replaces the previous HITRAN edition of 2012 and its updates during the intervening years. The HITRAN mol. absorption compilation is composed of five major components: the traditional line-by-line spectroscopic parameters required for high-resoln. radiative-transfer codes, IR absorption cross-sections for mols. not yet amenable to representation in a line-by-line form, collision-induced absorption data, aerosol indexes of refraction, and general tables such as partition sums that apply globally to the data. The new HITRAN is greatly extended in terms of accuracy, spectral coverage, addnl. absorption phenomena, added line-shape formalisms, and validity. Moreover, mols., isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth. Of considerable note, exptl. IR cross-sections for almost 300 addnl. mols. important in different areas of atm. science have been added to the database. The compilation can be accessed through www.hitran.org. Most of the HITRAN data have now been cast into an underlying relational database structure that offers many advantages over the long-standing sequential text-based structure. The new structure empowers the user in many ways. It enables the incorporation of an extended set of fundamental parameters per transition, sophisticated line-shape formalisms, easy user-defined output formats, and very convenient searching, filtering, and plotting of data. A powerful application programming interface making use of structured query language (SQL) features for higher-level applications of HITRAN is also provided.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2sXhtlKqtLbP&md5=93638425d6455d66541f48987b374a51
  63. 63
    Kramida, A.; Ralchenko, Yu.; Reader, J.; and NIST ASD Team NIST Atomic Spectra Database (ver. 5.7.1), [Online]. Available: https://physics.nist.gov/asd [2017, April 9]. National Institute of Standards and Technology: Gaithersburg, MD, 2019.
    Google Scholar
    There is no corresponding record for this reference.
  64. 64
    Gelin, M. F.; Blokhin, A. P.; Ostrozhenkova, E.; Apolonski, A.; Maiti, K. S. Theory helps experiment to reveal VOCs in human breath. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2021, 258, 119785,  DOI: 10.1016/j.saa.2021.119785
    Google Scholar
    There is no corresponding record for this reference.
  65. 65
    Quanjer, P.; Tammeling, G.; Cotes, J.; Pedersen, O.; Peslin, R.; Yernault, J.-C. Lung volumes and forced ventilatory flows. Eur. Respir. J. 1993, 6, 5– 40,  DOI: 10.1183/09041950.005s1693
    Google Scholar
    65
    Lung volumes and forced ventilatory flows
    Quanjer P H; Tammeling G J; Cotes J E; Pedersen O F; Peslin R; Yernault J C
    The European respiratory journal (1993), 6 Suppl 16 (), 5-40 ISSN:0903-1936.
    There is no expanded citation for this reference.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BC2cvovV2hsw%253D%253D&md5=2c79a67dc047746b91a4f60d93647020
  66. 66
    Cheng, W.; Dan, L.; Deng, X.; Feng, J.; Global Monthly Gridded Atmospheric Carbon Dioxide Concentrations under the Historical and Future Scenarios; Scientific Data, 2022, 9.
    Google Scholar
    There is no corresponding record for this reference.
  67. 67
    Haick, H.; Broza, Y. Y.; Mochalski, P.; Ruzsanyi, V.; Amann, A. Assessment, origin, and implementation of breath volatile cancer markers. Chem. Soc. Rev. 2014, 43, 1423– 1449,  DOI: 10.1039/C3CS60329F
    Google Scholar
    67
    Assessment, origin, and implementation of breath volatile cancer markers
    Haick, Hossam; Broza, Yoav Y.; Mochalski, Pawel; Ruzsanyi, Vera; Amann, Anton
    Chemical Society Reviews (2014), 43 (5), 1423-1449CODEN: CSRVBR; ISSN:0306-0012. (Royal Society of Chemistry)
    A review. A new non-invasive and potentially inexpensive frontier in the diagnosis of cancer relies on the detection of volatile org. compds. (VOCs) in exhaled breath samples. Breath can be sampled and analyzed in real-time, leading to fascinating and cost-effective clin. diagnostic procedures. Nevertheless, breath anal. is a very young field of research and faces challenges, mainly because the biochem. mechanisms behind the cancer-related VOCs are largely unknown. In this review, we present a list of 115 validated cancer-related VOCs published in the literature during the past decade, and classify them with respect to their "fat-to-blood" and "blood-to-air" partition coeffs. These partition coeffs. provide an estn. of the relative concns. of VOCs in alveolar breath, in blood and in the fat compartments of the human body. Addnl., we try to clarify controversial issues concerning possible exptl. malpractice in the field, and propose ways to translate the basic science results as well as the mechanistic understanding to tools (sensors) that could serve as point-of-care diagnostics of cancer. We end this review with a conclusion and a future perspective.
    >> More from SciFinder ®
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  68. 68
    Amann, A.; Miekisch, W.; Schubert, J.; Buszewski, B.; Ligor, T.; Jezierski, T.; Pleil, J.; Risby, T. Analysis of Exhaled Breath for Disease Detection. Annual Review of Analytical Chemistry 2014, 7, 455– 482,  DOI: 10.1146/annurev-anchem-071213-020043
    Google Scholar
    There is no corresponding record for this reference.
  69. 69
    Nicoll, J.; Cheung, P.-Y.; Aziz, K.; Rajani, V.; O’Reilly, M.; Pichler, G.; Schmölzer, G. M. Exhaled Carbon Dioxide and Neonatal Breathing Patterns in Preterm Infants after Birth. J. Pediatr. 2015, 167, 829– 833,  DOI: 10.1016/j.jpeds.2015.06.064
    Google Scholar
    There is no corresponding record for this reference.
  70. 70
    Robbins, R. C.; Borg, K. M.; Robinson, E. Carbon Monoxide in the Atmosphere. Journal of the Air Pollution Control Association 1968, 18, 106– 110,  DOI: 10.1080/00022470.1968.10469094
    Google Scholar
    There is no corresponding record for this reference.
  71. 71
    Ryter, S. W. Special issue on carbon monoxide and exhaled biomarkers in human disease. J. Breath Res. 2010, 4, 040201,  DOI: 10.1088/1752-7155/4/4/040201
    Google Scholar
    There is no corresponding record for this reference.
  72. 72
    Kumpitsch, C.; Fischmeister, F. P. S.; Mahnert, A.; Lackner, S.; Wilding, M.; Sturm, C.; Springer, A.; Madl, T.; Holasek, S.; Hogenauer, C.; Berg, I. A.; Schoepf, V.; Moissl-Eichinger, C.; Reduced B12 uptake and increased gastrointestinal formate are associated with archaeome-mediated breath methane emission in humans. Microbiome 2021, 9 DOI: 10.1186/s40168-021-01130-w .
    Google Scholar
    There is no corresponding record for this reference.
  73. 73
    Weaver, G. A.; Krause, J. A.; Miller, T. L.; Wolin, M. J. Incidence of methanogenic bacteria in a sigmoidoscopy population: an association of methanogenic bacteria and diverticulosis. Gut 1986, 27, 698– 704,  DOI: 10.1136/gut.27.6.698
    Google Scholar
    There is no corresponding record for this reference.
  74. 74
    Florin, T. H. J.; Zhu, G.; Kirk, K. M.; Martin, N. G. Shared and unique environmental factors determine the ecology of methanogens in humans and rats. American Journal of Gastroenterology 2000, 95, 2872– 2879,  DOI: 10.1111/j.1572-0241.2000.02319.x
    Google Scholar
    There is no corresponding record for this reference.
  75. 75
    Polag, D.; Keppler, F. Long-term monitoring of breath methane. Science of The Total Environment 2018, 624, 69– 77,  DOI: 10.1016/j.scitotenv.2017.12.097
    Google Scholar
    There is no corresponding record for this reference.
  76. 76
    Maiti, K. S.; Apolonski, A. Monitoring the Reaction of the Body State to Antibiotic Treatment against Helicobacter pylori via Infrared Spectroscopy: A Case Study. Molecules 2021, 26, 3474,  DOI: 10.3390/molecules26113474
    Google Scholar
    There is no corresponding record for this reference.

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  1. Wenlong Zhao, Xue Wang, Wang Li, Xiaoyan Peng, Peter Feng, Shukai Duan, Lidan Wang, Jin Chu. Fast identification of flammable chemicals based on broad learning system. Process Safety and Environmental Protection 2024, 191 , 1181-1192. https://doi.org/10.1016/j.psep.2024.09.007
  2. Susmita Roy, Jürgen Hauer, Kiran Sankar Maiti. Development of non-invasive diagnosis based on FTIR spectroscopy. Vibrational Spectroscopy 2024, 134 , 103724. https://doi.org/10.1016/j.vibspec.2024.103724
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  • Abstract

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    Figure 1

    Figure 1. Collection procedures of exhaled breath samples from neonates are depicted with the help of a model. Passive breath sample collection for neonates under various conditions, including (a) spontaneously breathing neonate, (b) air from the incubator with neonate, (c) neonate with CPAP delivered via ”infant flow” as respiratory support, and (d) intubated neonate.

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    Figure 2

    Figure 2. Sample population according to the GA of neonates. A blue color bar plot illustrates the mean GA for each group, with the lowest and highest GAs noted on the bars. Similarly, the red bars depict the lowest, highest, and mean BW. The left side scale corresponds to the mean GA, while the right side scale corresponds to the mean BW.

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    Figure 3

    Figure 3. Classification of collected samples according to the GA of the neonates as well as their life and respiratory support. The subscript in GA indicates the days, e.g., GA = 36+6 weeks mean 36 weeks and 6 days.

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    Figure 4

    Figure 4. Diagram of the experimental scheme for gaseous biofluid analysis by infrared spectroscopy. It consists of three major parts: (1) Collection─in this part, breath or headspace of liquid biofluids is collected; (2) Preparation─a water-suppressed sample is prepared for infrared spectroscopy when gaseous biofluids are passing through the “Water Condenser”; and (3) Analysis─water suppressed gaseous sample is collected in a multipass gas cell and measured with an FTIR spectrometer.

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    Figure 5

    Figure 5. Infrared absorption spectra of room air. Inset is the 104 times magnification of the same spectra at around 3000 cm–1.

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    Figure 6

    Figure 6. Infrared absorption spectra of ambient air, incubator’s air (with neonate), and exhaled air of a neonate with spontaneous (S) respiration, inlet and outlet air of a CPAP system. Spectra are zoomed around the absorption spectra of carbon dioxide.

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    Figure 7

    Figure 7. Infrared absorption spectra of ambient air along with exhaled breath from neonates with spontaneous (S) respiration, intubated (IT) and CPAP as respiratory support. The spectra are magnified around the absorption feature of carbon monoxide.

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    Figure 8

    Figure 8. Infrared absorption spectra of ambient air, the sample from a neonate with CPAP respiratory support, air from an incubator, and exhaled air of a neonate with spontaneous (S) respiration. Spectra are zoomed around the absorption feature of methane.

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    Figure 9

    Figure 9. (a–d) Infrared spectra of breath in the spectral region of methane for four different neonates. The spectral feature of methane is modified due to the presence of unknown endogenous metabolites.

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  • References

    This article references 76 other publications.

    1. 1
      Lawn, J. E. Small babies, big risks: global estimates of prevalence and mortality for vulnerable newborns to accelerate change and improve counting. Lancet 2023, 401, 1707– 1719,  DOI: 10.1016/S0140-6736(23)00522-6
      There is no corresponding record for this reference.
    2. 2
      Gallagher, K.; Shaw, C.; Parisaei, M.; Marlow, N.; Aladangady, N. Attitudes About Extremely Preterm Birth Among Obstetric and Neonatal Health Care Professionals in England. JAMA Network Open 2022, 5, e2241802  DOI: 10.1001/jamanetworkopen.2022.41802
      There is no corresponding record for this reference.
    3. 3
      Behrman, R. E., Butler, A. S., Eds. Preterm Birth; National Academies Press: Washington, D.C., 2007.
      There is no corresponding record for this reference.
    4. 4
      Zhao, Y.; Liu, G.; Liang, L.; Yu, Z. Relationship of plasma MBP and 8-oxo-dG with brain damage in preterm. Open Medicine 2022, 17, 1674– 1681,  DOI: 10.1515/med-2022-0566
      There is no corresponding record for this reference.
    5. 5
      Iroh Tam, P.-Y.; Bendel, C. M Diagnostics for neonatal sepsis: current approaches and future directions. Pediatr. Res. 2017, 82, 574– 583,  DOI: 10.1038/pr.2017.134
      There is no corresponding record for this reference.
    6. 6
      Ashorn, P. Small vulnerable newborns-big potential for impact. Lancet 2023, 401, 1692– 1706,  DOI: 10.1016/S0140-6736(23)00354-9
      There is no corresponding record for this reference.
    7. 7
      Linsell, L.; Malouf, R.; Morris, J.; Kurinczuk, J. J.; Marlow, N. Risk Factor Models for Neurodevelopmental Outcomes in Children Born Very Preterm or With Very Low Birth Weight: A Systematic Review of Methodology and Reporting. American Journal of Epidemiology 2017, 185, 601– 612,  DOI: 10.1093/aje/kww135
      There is no corresponding record for this reference.
    8. 8
      Tataranno, M. L.; Vijlbrief, D. C.; Dudink, J.; Benders, M. J. N. L. Precision Medicine in Neonates: A Tailored Approach to Neonatal Brain Injury. Front. Pediatr. 2021, 9 DOI: 10.3389/fped.2021.634092 .
      There is no corresponding record for this reference.
    9. 9
      Felderhoff-Müser, U.; Hüning, B. Biomarker und Neuromonitoring zur Entwicklungsprognose nach perinataler Hirnschädigung. Monatsschrift Kinderheilkunde 2022, 170, 688– 703,  DOI: 10.1007/s00112-022-01542-4
      There is no corresponding record for this reference.
    10. 10
      Marlow, N.; Wolke, D.; Bracewell, M. A.; Samara, M. Neurologic and Developmental Disability at Six Years of Age after Extremely Preterm Birth. New England Journal of Medicine 2005, 352, 9– 19,  DOI: 10.1056/NEJMoa041367
      There is no corresponding record for this reference.
    11. 11
      Spittle, A. J.; Orton, J. Cerebral palsy and developmental coordination disorder in children born preterm. Seminars in Fetal and Neonatal Medicine 2014, 19, 84– 89,  DOI: 10.1016/j.siny.2013.11.005
      There is no corresponding record for this reference.

      Long-term outcome for the tiniest or most immature babies.

    12. 12
      Ellenberg, J. H.; Nelson, K. B. Early Recognition of Infants at High Risk for Cerebral Palsy: Examination at Age Four Months. Developmental Medicine & Child Neurology 1981, 23, 705– 716,  DOI: 10.1111/j.1469-8749.1981.tb02059.x
      There is no corresponding record for this reference.
    13. 13
      Herskind, A.; Greisen, G.; Nielsen, J. B. Early identification and intervention in cerebral palsy. Developmental Medicine & Child Neurology 2015, 57, 29– 36,  DOI: 10.1111/dmcn.12531
      There is no corresponding record for this reference.
    14. 14
      Maiti, K. S.; Roy, S.; Lampe, R.; Apolonski, A. Breath indeed carries significant information about a disease. Potential biomarkers of cerebral palsy. J. Biophotonics 2020, 13, e202000125  DOI: 10.1002/jbio.202000125
      There is no corresponding record for this reference.
    15. 15
      McIntyre, S.; Morgan, C.; Walker, K.; Novak, I. Cerebral Palsy─Don’t Delay. Developmental Disabilities Research Reviews 2011, 17, 114– 129,  DOI: 10.1002/ddrr.1106
      There is no corresponding record for this reference.
    16. 16
      te Velde, A.; Morgan, C.; Novak, I.; Tantsis, E.; Badawi, N. Badawi Early Diagnosis and Classification of Cerebral Palsy: An Historical Perspective and Barriers to an Early Diagnosis. J. Clin. Med. 2019, 8, 1599,  DOI: 10.3390/jcm8101599
      There is no corresponding record for this reference.
    17. 17
      Meem, M.; Modak, J. K.; Mortuza, R.; Morshed, M.; Islam, M. S.; Saha, S. K. Biomarkers for diagnosis of neonatal infections: A systematic analysis of their potential as a point-of-care diagnostics. J. Glob. Health 2011, 1 (2), 201– 209
      There is no corresponding record for this reference.
    18. 18
      Celik, I. H.; Hanna, M.; Canpolat, F. E.; Pammi, M. Diagnosis of neonatal sepsis: the past, present and future. Pediatr. Res. 2022, 91 (2), 337– 350,  DOI: 10.1038/s41390-021-01696-z
      18
      Diagnosis of neonatal sepsis: the past, present and future
      Celik Istemi Han; Canpolat Fuat Emre; Celik Istemi Han; Hanna Morcos; Mohan Pammi; Canpolat Fuat Emre
      Pediatric research (2022), 91 (2), 337-350 ISSN:.
      Sepsis remains a significant cause of neonatal mortality and morbidity, especially in low- and middle-income countries. Neonatal sepsis presents with nonspecific signs and symptoms that necessitate tests to confirm the diagnosis. Early and accurate diagnosis of infection will improve clinical outcomes and decrease the overuse of antibiotics. Current diagnostic methods rely on conventional culture methods, which is time-consuming, and may delay critical therapeutic decisions. Nonculture-based techniques including molecular methods and mass spectrometry may overcome some of the limitations seen with culture-based techniques. Biomarkers including hematological indices, cell adhesion molecules, interleukins, and acute-phase reactants have been used for the diagnosis of neonatal sepsis. In this review, we examine past and current microbiological techniques, hematological indices, and inflammatory biomarkers that may aid sepsis diagnosis. The search for an ideal biomarker that has adequate diagnostic accuracy early in sepsis is still ongoing. We discuss promising strategies for the future that are being developed and tested that may help us diagnose sepsis early and improve clinical outcomes. IMPACT: Reviews the clinical relevance of currently available diagnostic tests for sepsis. Summarizes the diagnostic accuracy of novel biomarkers for neonatal sepsis. Outlines future strategies including the use of omics technology, personalized medicine, and point of care tests.
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    19. 19
      Mahwasane, T.; Maputle, M. S.; Simane-Netshisaulu, K. G.; Malwela, T. Provision of Care to Preterm Infants at Resource Limited Health Facilities of Mopani District, South Africa. Annals of Global Health 2020, 86, 10,  DOI: 10.5334/aogh.2555
      There is no corresponding record for this reference.
    20. 20
      Boland, R. A.; Davis, P. G.; Dawson, J. A.; Doyle, L. W. What are we telling the parents of extremely preterm babies?. Australian and New Zealand Journal of Obstetrics and Gynaecology 2016, 56, 274– 281,  DOI: 10.1111/ajo.12448
      There is no corresponding record for this reference.
    21. 21
      Patel, R. M.; Rysavy, M. A.; Bell, E. F.; Tyson, J. E. Survival of Infants Born at Periviable Gestational Ages. Clinics in Perinatology 2017, 44, 287– 303,  DOI: 10.1016/j.clp.2017.01.009
      There is no corresponding record for this reference.
    22. 22
      Maiti, K. S.; Lewton, M.; Fill, E.; Apolonski, A. Human beings as islands of stability: Monitoring body states using breath profiles. Sci. Rep. 2019, 9, 16167,  DOI: 10.1038/s41598-019-51417-0
      There is no corresponding record for this reference.
    23. 23
      Qiu, S.; Cai, Y.; Yao, H.; Lin, C.; Xie, Y.; Tang, S.; Zhang, A.; Small molecule metabolites: discovery of biomarkers and therapeutic targets. Sig. Transduct. Target Ther. 2023, 8 DOI: 10.1038/s41392-023-01399-3 .
      There is no corresponding record for this reference.
    24. 24
      Shirasu, M.; Touhara, K. The scent of disease: volatile organic compounds of the human body related to disease and disorder. Journal of Biochemistry 2011, 150, 257,  DOI: 10.1093/jb/mvr090
      24
      The scent of disease: volatile organic compounds of the human body related to disease and disorder
      Shirasu, Mika; Touhara, Kazushige
      Journal of Biochemistry (2011), 150 (3), 257-266CODEN: JOBIAO; ISSN:0021-924X. (Oxford University Press)
      A review. Hundreds of volatile org. compds. (VOCs) are emitted from the human body, and the components of VOCs usually reflect the metabolic condition of an individual. Therefore, contracting an infectious or metabolic disease often results in a change in body odor. Recent progresses in anal. techniques allow rapid analyses of VOCs derived from breath, blood, skin and urine. Disease-specific VOCs can be used as diagnostic olfactory biomarkers of infectious diseases, metabolic diseases, genetic disorders and other kinds of diseases. Elucidation of pathophysiol. mechanisms underlying prodn. of disease-specific VOCs may provide novel insights into therapeutic approaches for treatments for various diseases. This review summarizes the current knowledge on chem. and clin. aspects of body-derived VOCs, and provides a brief outlook at the future of olfactory diagnosis.
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    25. 25
      Drabińska, N.; Flynn, C.; Ratcliffe, N.; Belluomo, I. A literature survey of all volatiles from healthy human breath and bodily fluids: the human volatilome. Journal of Breath Research 2021, 15, 034001,  DOI: 10.1088/1752-7163/abf1d0
      There is no corresponding record for this reference.
    26. 26
      Metzler, D. E. Biochemistry: The Chemical Reactions of Living Cells; Academic Press: New York, 2003.
      There is no corresponding record for this reference.
    27. 27
      Ahern, K. Biochemistry and Molecular Biology: How Life Works; Teaching Company, LLC: Chantilly, VA, 2019.
      There is no corresponding record for this reference.
    28. 28
      Huber, M.; Kepesidis, K. V.; Voronina, L.; Bozic, M.; Trubetskov, M.; Harbeck, N.; Krausz, F.; Zigman, M. Stability of person-specific blood-based infrared molecular fingerprints opens up prospects for health monitoring. Nat. Commun. 2021, 12, 1511,  DOI: 10.1038/s41467-021-21668-5
      28
      Stability of person-specific blood-based infrared molecular fingerprints opens up prospects for health monitoring
      Huber, Marinus; Kepesidis, Kosmas V.; Voronina, Liudmila; Bozic, Masa; Trubetskov, Michael; Harbeck, Nadia; Krausz, Ferenc; Zigman, Mihaela
      Nature Communications (2021), 12 (1), 1511CODEN: NCAOBW; ISSN:2041-1723. (Nature Research)
      Health state transitions are reflected in characteristic changes in the mol. compn. of biofluids. Detecting these changes in parallel, across a broad spectrum of mol. species, could contribute to the detection of abnormal physiologies. Fingerprinting of biofluids by IR vibrational spectroscopy offers that capacity. Whether its potential for health monitoring can indeed be exploited critically depends on how stable IR mol. fingerprints (IMFs) of individuals prove to be over time. Here we report a proof-of-concept study that addresses this question. Using Fourier-transform IR spectroscopy, we have fingerprinted blood serum and plasma samples from 31 healthy, non-symptomatic individuals, who were sampled up to 13 times over a period of 7 wk and again after 6 mo. The measurements were performed directly on liq. serum and plasma samples, yielding a time- and cost-effective workflow and a high degree of reproducibility. The resulting IMFs were found to be highly stable over clin. relevant time scales. Single measurements yielded a multiplicity of person-specific spectral markers, allowing individual mol. phenotypes to be detected and followed over time. This previously unknown temporal stability of individual biochem. fingerprints forms the basis for future applications of blood-based IR spectral fingerprinting as a multiomics-based mode of health monitoring.
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    29. 29
      Maiti, K. S.; Fill, E.; Strittmatter, F.; Volz, Y.; Sroka, R.; Apolonski, A. Towards reliable diagnostics of prostate cancer via breath. Sci. Rep. 2021, 11, 18381,  DOI: 10.1038/s41598-021-96845-z
      There is no corresponding record for this reference.
    30. 30
      Maiti, K. S.; Fill, E.; Strittmatter, F.; Volz, Y.; Sroka, R.; Apolonski, A. Standard operating procedure to reveal prostate cancer specific volatile organic molecules by infrared spectroscopy. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2024, 304, 123266,  DOI: 10.1016/j.saa.2023.123266
      There is no corresponding record for this reference.
    31. 31
      Gowda, G. N.; Zhang, S.; Gu, H.; Asiago, V.; Shanaiah, N.; Raftery, D. Metabolomics-based methods for early disease diagnostics. Expert Review of Molecular Diagnostics 2008, 8, 617– 633,  DOI: 10.1586/14737159.8.5.617
      31
      Metabolomics-based methods for early disease diagnostics
      Gowda, Ga nagana; Zhang, Shucha; Gu, Haiwei; Asiago, Vincent; Shanaiah, Narasimhamurthy; Raftery, Daniel
      Expert Review of Molecular Diagnostics (2008), 8 (5), 617-633CODEN: ERMDCW; ISSN:1473-7159. (Expert Reviews Ltd.)
      A review. The emerging field of metabolomics, in which a large no. of small-mol. metabolites from body fluids or tissues are detected quant. in a single step, promises immense potential for early diagnosis, therapy monitoring and for understanding the pathogenesis of many diseases. Metabolomics methods are mostly focused on the information-rich anal. techniques of NMR spectroscopy and mass spectrometry (MS). Anal. of the data from these high-resoln. methods using advanced chemometric approaches provides a powerful platform for translational and clin. research and diagnostic applications. In this review, the current trends and recent advances in NMR- and MS-based metabolomics are described with a focus on the development of advanced NMR and MS methods, improved multivariate statistical data anal. and recent applications in the area of cancer, diabetes, inborn errors of metab. and cardiovascular diseases.
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    32. 32
      Beauchamp, J. D.; Davis, C.; Pleil, J. D. Breathborne Biomarkers and the Human Volatilome; Elsevier: New Amsterdam, 2020.
      There is no corresponding record for this reference.
    33. 33
      Pauling, L.; Robinson, A. B.; Teranishi, R.; Cary, P. Quantitative Analysis of Urine Vapor and Breath by Gas-Liquid Partition Chromatography. Proc. Natl. Acad. Sci. U. S. A. 1971, 68, 2374– 2376,  DOI: 10.1073/pnas.68.10.2374
      33
      Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography
      Pauling, Linus; Robinson, Arthur B.; Teranishi, Roy; Cary, Paul
      Proceedings of the National Academy of Sciences of the United States of America (1971), 68 (10), 2374-6CODEN: PNASA6; ISSN:0027-8424.
      When a human being is placed for several days on a completely define diet, consisting almost entirely of small mols. that are absorbed from the stomach into the blood, intestinal flora disappear because of lack of nutrition. By this technique, the compn. of body fluids can be made const. (std. deviation about 10%) after a few days, permitting significant quant. analyses to be performed. A method of temp.-programmed gas chromatog. was developed for this purpose. It permits the quant. detn. of about 250 substances in a sample of breath, and of about 280 substances in a sample of urine vapor. The technique should be useful in the application of the principles of orthomol. medicine.
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    34. 34
      Sukul, P.; Schubert, J. K.; Zanaty, K.; Trefz, P.; Sinha, A.; Kamysek, S.; Miekisch, W.; Exhaled breath compositions under varying respiratory rhythms reflects ventilatory variations: translating breathomics towards respiratory medicine. Sci. Rep. 2020, 10 DOI: 10.1038/s41598-020-70993-0 .
      There is no corresponding record for this reference.
    35. 35
      Decrue, F.; Singh, K. D.; Gisler, A.; Awchi, M. Combination of Exhaled Breath Analysis with Parallel Lung Function and FeNO Measurements in Infants. Anal. Chem. 2021, 93, 15579– 15583,  DOI: 10.1021/acs.analchem.1c02036
      There is no corresponding record for this reference.
    36. 36
      Romijn, M.; van Kaam, A. H.; Fenn, D.; Bos, L. D. Exhaled Volatile Organic Compounds for Early Prediction of Bronchopulmonary Dysplasia in Infants Born Preterm. Journal of Pediatrics 2023, 257, 113368,  DOI: 10.1016/j.jpeds.2023.02.014
      There is no corresponding record for this reference.
    37. 37
      Ophelders, D. R. M. G.; Boots, A. W.; Hütten, M. C.; Al-Nasiry, S.; Jellema, R. K.; Spiller, O. B.; van Schooten, F.-J.; Smolinska, A.; Wolfs, T. G. A. M. Screening of Chorioamnionitis Using Volatile Organic Compound Detection in Exhaled Breath: A Pre-clinical Proof of Concept Study. Front. Pediatr. 2021, 9, 488,  DOI: 10.3389/fped.2021.617906
      There is no corresponding record for this reference.
    38. 38
      Maiti, K. S. Non-Invasive Disease Specific Biomarker Detection Using Infrared Spectroscopy: A Review. Molecules 2023, 28, 2320,  DOI: 10.3390/molecules28052320
      There is no corresponding record for this reference.
    39. 39
      Pham, Y. L.; Beauchamp, J. Breath Biomarkers in Diagnostic Applications. Molecules 2021, 26, 5514,  DOI: 10.3390/molecules26185514
      There is no corresponding record for this reference.
    40. 40
      Li, C.; Chu, S.; Tan, S.; Yin, X.; Jiang, Y.; Dai, X.; Gong, X.; Fang, X.; Tian, D.; Towards Higher Sensitivity of Mass Spectrometry: A Perspective From the Mass Analyzers. Front. Chem. 2021, 9 DOI: 10.3389/fchem.2021.813359 .
      There is no corresponding record for this reference.
    41. 41
      Hanna, G. B.; Boshier, P. R.; Markar, S. R.; Romano, A. Accuracy and Methodologic Challenges of Volatile Organic Compound–Based Exhaled Breath Tests for Cancer Diagnosis. JAMA Oncology 2019, 5, e182815  DOI: 10.1001/jamaoncol.2018.2815
      There is no corresponding record for this reference.
    42. 42
      Karakaya, D.; Ulucan, O.; Turkan, M. Electronic Nose and Its Applications: A Survey. Int. J. Autom. Comput. 2020, 17, 179– 209,  DOI: 10.1007/s11633-019-1212-9
      There is no corresponding record for this reference.
    43. 43
      Ye, Z.; Liu, Y.; Li, Q. Recent Progress in Smart Electronic Nose Technologies Enabled with Machine Learning Methods. Sensors 2021, 21, 7620,  DOI: 10.3390/s21227620
      There is no corresponding record for this reference.
    44. 44
      Kwon, O. S.; Song, H. S.; Park, S. J.; Lee, S. H.; An, J. H. An Ultrasensitive, Selective, Multiplexed Superbioelectronic Nose That Mimics the Human Sense of Smell. Nano Lett. 2015, 15, 6559– 6567,  DOI: 10.1021/acs.nanolett.5b02286
      44
      An Ultrasensitive, Selective, Multiplexed Superbioelectronic Nose That Mimics the Human Sense of Smell
      Kwon, Oh Seok; Song, Hyun Seok; Park, Seon Joo; Lee, Seung Hwan; An, Ji Hyun; Park, Jin Wook; Yang, Heehong; Yoon, Hyeonseok; Bae, Joonwon; Park, Tai Hyun; Jang, Jyongsik
      Nano Letters (2015), 15 (10), 6559-6567CODEN: NALEFD; ISSN:1530-6984. (American Chemical Society)
      Human sensory-mimicking systems, such as electronic brains, tongues, skin, and ears, have been promoted for use in improving social welfare. However, no significant achievements have been made in mimicking the human nose due to the complexity of olfactory sensory neurons. Combinational coding of human olfactory receptors (hORs) is essential for odorant discrimination in mixts., and the development of hOR-combined multiplexed systems has progressed slowly. Here, the authors report the first demonstration of an artificial multiplexed superbioelectronic nose (MSB-nose) that mimics the human olfactory sensory system, leading to high-performance odorant discriminatory ability in mixts. Specifically, portable MSB-noses were constructed using highly uniform graphene micropatterns (GMs) that were conjugated with two different hORs, which were employed as transducers in a liq.-ion gated field-effect transistor (FET). Field-induced signals from the MSB-nose were monitored and provided high sensitivity and selectivity toward target odorants (min. detectable level: 0.1 fM). More importantly, the potential of the MSB-nose as a tool to encode hOR combinations was demonstrated using principal component anal.
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    45. 45
      Di Natale, C.; Paolesse, R.; Martinelli, E.; Capuano, R. Solid-state gas sensors for breath analysis: A review. Anal. Chim. Acta 2014, 824, 1– 17,  DOI: 10.1016/j.aca.2014.03.014
      45
      Solid-state gas sensors for breath analysis: A review
      Di Natale, Corrado; Paolesse, Roberto; Martinelli, Eugenio; Capuano, Rosamaria
      Analytica Chimica Acta (2014), 824 (), 1-17CODEN: ACACAM; ISSN:0003-2670. (Elsevier B.V.)
      A review. The anal. of volatile compds. is an efficient method to appraise information about the chem. compn. of liqs. and solids. This principle is applied to several practical applications, such as food anal. where many important features (e.g. freshness) can be directly inferred from the anal. of volatile compds. The same approach can also be applied to a human body where the volatile compds., collected from the skin, the breath or in the headspace of fluids, might contain information that could be used to diagnose several kinds of diseases. In particular, breath is widely studied and many diseases can be potentially detected from breath anal.The most fascinating property of breath anal. is the non-invasiveness of the sample collection. Solid-state sensors are considered the natural complement to breath anal., matching the non-invasiveness with typical sensor features such as low-cost, easiness of use, portability, and the integration with the information networks. Sensors based breath anal. is then expected to dramatically extend the diagnostic capabilities enabling the screening of large populations for the early diagnosis of pathologies.In the last years there has been an increased attention to the development of sensors specifically aimed to this purpose. These investigations involve both specific sensors designed to detect individual compds. and non-specific sensors, operated in array configurations, aimed at clustering subjects according to their health conditions. In this paper, the recent significant applications of these sensors to breath anal. are reviewed and discussed.
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    46. 46
      Wilson, E.; Decius, J.; Cross, P. Molecular Vibrations: The Theory of Infrared and Raman Vibrational Spectra. Dover Books on Chemistry Series; Dover Publications: New York, 1980.
      There is no corresponding record for this reference.
    47. 47
      Maiti, K. S. Vibrational spectroscopy of Methyl benzoate. Phys. Chem. Chem. Phys. 2015, 17, 19735– 19744,  DOI: 10.1039/C5CP02281A
      There is no corresponding record for this reference.
    48. 48
      Roy, S.; Maiti, K. S. Structural sensitivity of CH vibrational band in methyl benzoate. Spectrochim. Acta Mol. Biomol. Spectrosc. 2018, 196, 289– 294,  DOI: 10.1016/j.saa.2018.02.031
      There is no corresponding record for this reference.
    49. 49
      Maiti, K. S. Ultrafast vibrational coupling between C–H and C = O band of cyclic amide 2-Pyrrolidinone revealed by 2DIR spectroscopy. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2020, 228, 117749,  DOI: 10.1016/j.saa.2019.117749
      There is no corresponding record for this reference.
    50. 50
      Buchan, E.; Kelleher, L.; Clancy, M.; Stanley Rickard, J. J.; Oppenheimer, P. G. Spectroscopic molecular-fingerprint profiling of saliva. Anal. Chim. Acta 2021, 1185, 339074,  DOI: 10.1016/j.aca.2021.339074
      50
      Spectroscopic molecular-fingerprint profiling of saliva
      Buchan, Emma; Kelleher, Liam; Clancy, Michael; Stanley Rickard, Jonathan James; Oppenheimer, Pola Goldberg
      Analytica Chimica Acta (2021), 1185 (), 339074CODEN: ACACAM; ISSN:0003-2670. (Elsevier B.V.)
      Saliva anal. has been gaining interest as a potential non-invasive source of disease indicative biomarkers due to being a complex biofluid correlating with blood-based constituents on a mol. level. For saliva to cement its usage for anal. applications, it is paramount to gain underpinning mol. knowledge and establish a 'baseline' of the salivary compn. in healthy individuals as well as characterize how these factors are impacting its performance as potential anal. biofluid. Here, we have systematically studied the mol. spectral fingerprint of saliva, including the changes assocd. with gender, age, and time. Via hybrid artificial neural network algorithms and Raman spectroscopy, we have developed a non-destructive mol. profiling approach enabling the assessment of salivary spectral changes yielding the detn. of gender and age of the biofluid source. Our classification algorithm successfully identified the gender and age from saliva with high classification accuracy. Discernible spectral mol. 'barcodes' were subsequently constructed for each class and found to primarily stem from amino acid, protein, and lipid changes in saliva. This unique combination of Raman spectroscopy and advanced machine learning techniques lays the platform for a variety of applications in forensics and biosensing.
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    51. 51
      Maiti, K. S. Two-dimensional Infrared Spectroscopy Reveals Better Insights of Structure and Dynamics of Protein. Molecules 2021, 26, 6893,  DOI: 10.3390/molecules26226893
      There is no corresponding record for this reference.
    52. 52
      Takamura, A.; Watanabe, K.; Akutsu, T.; Ozawa, T. Soft and Robust Identification of Body Fluid Using Fourier Transform Infrared Spectroscopy and Chemometric Strategies for Forensic Analysis. Sci. Rep. 2018, 8, 8459,  DOI: 10.1038/s41598-018-26873-9
      52
      Soft and Robust Identification of Body Fluid Using Fourier Transform Infrared Spectroscopy and Chemometric Strategies for Forensic Analysis
      Takamura Ayari; Watanabe Ken; Akutsu Tomoko; Takamura Ayari; Ozawa Takeaki
      Scientific reports (2018), 8 (1), 8459 ISSN:.
      Body fluid (BF) identification is a critical part of a criminal investigation because of its ability to suggest how the crime was committed and to provide reliable origins of DNA. In contrast to current methods using serological and biochemical techniques, vibrational spectroscopic approaches provide alternative advantages for forensic BF identification, such as non-destructivity and versatility for various BF types and analytical interests. However, unexplored issues remain for its practical application to forensics; for example, a specific BF needs to be discriminated from all other suspicious materials as well as other BFs, and the method should be applicable even to aged BF samples. Herein, we describe an innovative modeling method for discriminating the ATR FT-IR spectra of various BFs, including peripheral blood, saliva, semen, urine and sweat, to meet the practical demands described above. Spectra from unexpected non-BF samples were efficiently excluded as outliers by adopting the Q-statistics technique. The robustness of the models against aged BFs was significantly improved by using the discrimination scheme of a dichotomous classification tree with hierarchical clustering. The present study advances the use of vibrational spectroscopy and a chemometric strategy for forensic BF identification.
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    53. 53
      Apolonski, A.; Roy, S.; Lampe, R.; Sankar Maiti, K. Molecular identification of bio-fluids in gas phase using infrared spectroscopy. Appl. Opt. 2020, 59, E36– E41,  DOI: 10.1364/AO.388362
      There is no corresponding record for this reference.
    54. 54
      Mochalski, P.; King, J.; Unterkofler, K.; Amann, A. Stability of selected volatile breath constituents in Tedlar, Kynar and Flexfilm sampling bags. Analyst 2013, 138, 1405– 1418,  DOI: 10.1039/c2an36193k
      There is no corresponding record for this reference.
    55. 55
      Baker, J. The Machine in the Nursery: Incubator Technology and the Origins of Newborn Intensive Care; Johns Hopkins Introductory Studies in the History Series; Johns Hopkins University Press: Baltimore, MD, 1996.
      There is no corresponding record for this reference.
    56. 56
      Kidman, A. M.; Manley, B. J.; Boland, R. A.; Malhotra, A. Higher versus lower nasal continuous positive airway pressure for extubation of extremely preterm infants in Australia (ÉCLAT): a multicentre, randomised, superiority trial. Lancet Child & Adolescent Health 2023, 7, 844– 851,  DOI: 10.1016/S2352-4642(23)00235-3
      There is no corresponding record for this reference.
    57. 57
      Rocha, G.; Soares, P.; Gonçalves, A.; Silva, A. I. Respiratory Care for the Ventilated Neonate. Canadian Respiratory Journal 2018, 2018, 1– 12,  DOI: 10.1155/2018/7472964
      There is no corresponding record for this reference.
    58. 58
      Maiti, K. S.; Lewton, M.; Fill, E.; Apolonski, A. Sensitive spectroscopic breath analysis by water condensation. Journal of Breath Research 2018, 12, 046003,  DOI: 10.1088/1752-7163/aad207
      There is no corresponding record for this reference.
    59. 59
      Apolonski, A.; Maiti, K. S. Towards a standard operating procedure for revealing hidden volatile organic compounds in breath: the Fourier-transform IR spectroscopy case. Appl. Opt. 2021, 60, 4217– 4224,  DOI: 10.1364/AO.421994
      There is no corresponding record for this reference.
    60. 60
      Roy, S.; Maiti, K. S. Baseline correction for the infrared spectra of exhaled breath. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2024, 318, 124473,  DOI: 10.1016/j.saa.2024.124473
      There is no corresponding record for this reference.
    61. 61
      Johnson, T. J.; Sams, R. L.; Sharpe, S. W. The PNNL quantitative infrared database for gas-phase sensing: a spectral library for environmental, hazmat, and public safety standoff detection. Chemical and Biological Point Sensors for Homeland Defense 2004, 159– 167,  DOI: 10.1117/12.515604
      There is no corresponding record for this reference.
    62. 62
      Gordon, I.E.; Rothman, L.S.; Hill, C.; Kochanov, R.V.; Tan, Y.; Bernath, P.F.; Birk, M.; Boudon, V.; Campargue, A.; Chance, K.V.; Drouin, B.J.; Flaud, J.-M.; Gamache, R.R.; Hodges, J.T.; Jacquemart, D.; Perevalov, V.I.; Perrin, A.; Shine, K.P.; Smith, M.-A.H.; Tennyson, J.; Toon, G.C.; Tran, H.; Tyuterev, V.G.; Barbe, A.; Csaszar, A.G.; Devi, V.M.; Furtenbacher, T.; Harrison, J.J.; Hartmann, J.-M.; Jolly, A.; Johnson, T.J.; Karman, T.; Kleiner, I.; Kyuberis, A.A.; Loos, J.; Lyulin, O.M.; Massie, S.T.; Mikhailenko, S.N.; Moazzen-Ahmadi, N.; Muller, H.S.P.; Naumenko, O.V.; Nikitin, A.V.; Polyansky, O.L.; Rey, M.; Rotger, M.; Sharpe, S.W.; Sung, K.; Starikova, E.; Tashkun, S.A.; Auwera, J. V.; Wagner, G.; Wilzewski, J.; Wcisło, P.; Yu, S.; Zak, E.J. The HITRAN2016 molecular spectroscopic database. J. Quant. Spectrosc. Radiat. Transfer 2017, 203, 3– 69,  DOI: 10.1016/j.jqsrt.2017.06.038
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      The HITRAN2016 molecular spectroscopic database
      Gordon, I. E.; Rothman, L. S.; Hill, C.; Kochanov, R. V.; Tan, Y.; Bernath, P. F.; Birk, M.; Boudon, V.; Campargue, A.; Chance, K. V.; Drouin, B. J.; Flaud, J.-M.; Gamache, R. R.; Hodges, J. T.; Jacquemart, D.; Perevalov, V. I.; Perrin, A.; Shine, K. P.; Smith, M.-A. H.; Tennyson, J.; Toon, G. C.; Tran, H.; Tyuterev, V. G.; Barbe, A.; Csaszar, A. G.; Devi, V. M.; Furtenbacher, T.; Harrison, J. J.; Hartmann, J.-M.; Jolly, A.; Johnson, T. J.; Karman, T.; Kleiner, I.; Kyuberis, A. A.; Loos, J.; Lyulin, O. M.; Massie, S. T.; Mikhailenko, S. N.; Moazzen-Ahmadi, N.; Muller, H. S. P.; Naumenko, O. V.; Nikitin, A. V.; Polyansky, O. L.; Rey, M.; Rotger, M.; Sharpe, S. W.; Sung, K.; Starikova, E.; Tashkun, S. A.; Vander Auwera, J.; Wagner, G.; Wilzewski, J.; Wcislo, P.; Yu, S.; Zak, E. J.
      Journal of Quantitative Spectroscopy & Radiative Transfer (2017), 203 (), 3-69CODEN: JQSRAE; ISSN:0022-4073. (Elsevier Ltd.)
      This paper describes the contents of the 2016 edition of the HITRAN mol. spectroscopic compilation. The new edition replaces the previous HITRAN edition of 2012 and its updates during the intervening years. The HITRAN mol. absorption compilation is composed of five major components: the traditional line-by-line spectroscopic parameters required for high-resoln. radiative-transfer codes, IR absorption cross-sections for mols. not yet amenable to representation in a line-by-line form, collision-induced absorption data, aerosol indexes of refraction, and general tables such as partition sums that apply globally to the data. The new HITRAN is greatly extended in terms of accuracy, spectral coverage, addnl. absorption phenomena, added line-shape formalisms, and validity. Moreover, mols., isotopologues, and perturbing gases have been added that address the issues of atmospheres beyond the Earth. Of considerable note, exptl. IR cross-sections for almost 300 addnl. mols. important in different areas of atm. science have been added to the database. The compilation can be accessed through www.hitran.org. Most of the HITRAN data have now been cast into an underlying relational database structure that offers many advantages over the long-standing sequential text-based structure. The new structure empowers the user in many ways. It enables the incorporation of an extended set of fundamental parameters per transition, sophisticated line-shape formalisms, easy user-defined output formats, and very convenient searching, filtering, and plotting of data. A powerful application programming interface making use of structured query language (SQL) features for higher-level applications of HITRAN is also provided.
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    63. 63
      Kramida, A.; Ralchenko, Yu.; Reader, J.; and NIST ASD Team NIST Atomic Spectra Database (ver. 5.7.1), [Online]. Available: https://physics.nist.gov/asd [2017, April 9]. National Institute of Standards and Technology: Gaithersburg, MD, 2019.
      There is no corresponding record for this reference.
    64. 64
      Gelin, M. F.; Blokhin, A. P.; Ostrozhenkova, E.; Apolonski, A.; Maiti, K. S. Theory helps experiment to reveal VOCs in human breath. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2021, 258, 119785,  DOI: 10.1016/j.saa.2021.119785
      There is no corresponding record for this reference.
    65. 65
      Quanjer, P.; Tammeling, G.; Cotes, J.; Pedersen, O.; Peslin, R.; Yernault, J.-C. Lung volumes and forced ventilatory flows. Eur. Respir. J. 1993, 6, 5– 40,  DOI: 10.1183/09041950.005s1693
      65
      Lung volumes and forced ventilatory flows
      Quanjer P H; Tammeling G J; Cotes J E; Pedersen O F; Peslin R; Yernault J C
      The European respiratory journal (1993), 6 Suppl 16 (), 5-40 ISSN:0903-1936.
      There is no expanded citation for this reference.
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    66. 66
      Cheng, W.; Dan, L.; Deng, X.; Feng, J.; Global Monthly Gridded Atmospheric Carbon Dioxide Concentrations under the Historical and Future Scenarios; Scientific Data, 2022, 9.
      There is no corresponding record for this reference.
    67. 67
      Haick, H.; Broza, Y. Y.; Mochalski, P.; Ruzsanyi, V.; Amann, A. Assessment, origin, and implementation of breath volatile cancer markers. Chem. Soc. Rev. 2014, 43, 1423– 1449,  DOI: 10.1039/C3CS60329F
      67
      Assessment, origin, and implementation of breath volatile cancer markers
      Haick, Hossam; Broza, Yoav Y.; Mochalski, Pawel; Ruzsanyi, Vera; Amann, Anton
      Chemical Society Reviews (2014), 43 (5), 1423-1449CODEN: CSRVBR; ISSN:0306-0012. (Royal Society of Chemistry)
      A review. A new non-invasive and potentially inexpensive frontier in the diagnosis of cancer relies on the detection of volatile org. compds. (VOCs) in exhaled breath samples. Breath can be sampled and analyzed in real-time, leading to fascinating and cost-effective clin. diagnostic procedures. Nevertheless, breath anal. is a very young field of research and faces challenges, mainly because the biochem. mechanisms behind the cancer-related VOCs are largely unknown. In this review, we present a list of 115 validated cancer-related VOCs published in the literature during the past decade, and classify them with respect to their "fat-to-blood" and "blood-to-air" partition coeffs. These partition coeffs. provide an estn. of the relative concns. of VOCs in alveolar breath, in blood and in the fat compartments of the human body. Addnl., we try to clarify controversial issues concerning possible exptl. malpractice in the field, and propose ways to translate the basic science results as well as the mechanistic understanding to tools (sensors) that could serve as point-of-care diagnostics of cancer. We end this review with a conclusion and a future perspective.
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    68. 68
      Amann, A.; Miekisch, W.; Schubert, J.; Buszewski, B.; Ligor, T.; Jezierski, T.; Pleil, J.; Risby, T. Analysis of Exhaled Breath for Disease Detection. Annual Review of Analytical Chemistry 2014, 7, 455– 482,  DOI: 10.1146/annurev-anchem-071213-020043
      There is no corresponding record for this reference.
    69. 69
      Nicoll, J.; Cheung, P.-Y.; Aziz, K.; Rajani, V.; O’Reilly, M.; Pichler, G.; Schmölzer, G. M. Exhaled Carbon Dioxide and Neonatal Breathing Patterns in Preterm Infants after Birth. J. Pediatr. 2015, 167, 829– 833,  DOI: 10.1016/j.jpeds.2015.06.064
      There is no corresponding record for this reference.
    70. 70
      Robbins, R. C.; Borg, K. M.; Robinson, E. Carbon Monoxide in the Atmosphere. Journal of the Air Pollution Control Association 1968, 18, 106– 110,  DOI: 10.1080/00022470.1968.10469094
      There is no corresponding record for this reference.
    71. 71
      Ryter, S. W. Special issue on carbon monoxide and exhaled biomarkers in human disease. J. Breath Res. 2010, 4, 040201,  DOI: 10.1088/1752-7155/4/4/040201
      There is no corresponding record for this reference.
    72. 72
      Kumpitsch, C.; Fischmeister, F. P. S.; Mahnert, A.; Lackner, S.; Wilding, M.; Sturm, C.; Springer, A.; Madl, T.; Holasek, S.; Hogenauer, C.; Berg, I. A.; Schoepf, V.; Moissl-Eichinger, C.; Reduced B12 uptake and increased gastrointestinal formate are associated with archaeome-mediated breath methane emission in humans. Microbiome 2021, 9 DOI: 10.1186/s40168-021-01130-w .
      There is no corresponding record for this reference.
    73. 73
      Weaver, G. A.; Krause, J. A.; Miller, T. L.; Wolin, M. J. Incidence of methanogenic bacteria in a sigmoidoscopy population: an association of methanogenic bacteria and diverticulosis. Gut 1986, 27, 698– 704,  DOI: 10.1136/gut.27.6.698
      There is no corresponding record for this reference.
    74. 74
      Florin, T. H. J.; Zhu, G.; Kirk, K. M.; Martin, N. G. Shared and unique environmental factors determine the ecology of methanogens in humans and rats. American Journal of Gastroenterology 2000, 95, 2872– 2879,  DOI: 10.1111/j.1572-0241.2000.02319.x
      There is no corresponding record for this reference.
    75. 75
      Polag, D.; Keppler, F. Long-term monitoring of breath methane. Science of The Total Environment 2018, 624, 69– 77,  DOI: 10.1016/j.scitotenv.2017.12.097
      There is no corresponding record for this reference.
    76. 76
      Maiti, K. S.; Apolonski, A. Monitoring the Reaction of the Body State to Antibiotic Treatment against Helicobacter pylori via Infrared Spectroscopy: A Case Study. Molecules 2021, 26, 3474,  DOI: 10.3390/molecules26113474
      There is no corresponding record for this reference.