Breath Analysis Research Articles

Non-steroidal anti-inflammatory drugs and biomarkers: A new paradigm in colorectal cancer.

Colorectal cancer is a sporadic, hereditary, or familial based disease in its origin, caused due to diverse set of mutations in large intestinal epithelial cells. Colorectal cancer (CRC) is a common and deadly disease that accounts for the 4th worldwide highly variable malignancy. For the early detection of CRC, the most common predictive biomarker found endogenously are KRAS and ctDNA/cfDNA along with SEPT9 methylated DNA. Early detection and screening for CRC are necessary and multiple methods can be employed to screen and perform early diagnosis of CRC. Colonoscopy, an invasive method is most prevalent for diagnosing CRC or confirming the positive result as compared to other screening methods whereas several non-invasive techniques such as molecular analysis of breath, urine, blood, and stool can also be performed for early detection. Interestingly, widely used medicines known as non-steroidal anti-inflammatory drugs (NSAIDs) to reduce pain and inflammation have reported chemopreventive impact on gastrointestinal malignancies, especially CRC in several epidemiological and preclinical types of research. NSAID acts by inhibiting two cyclooxygenase enzymes, thereby preventing the synthesis of prostaglandins (PGs) and causing NSAID-induced apoptosis and growth inhibition in CRC cells. This review paper majorly focuses on the diversity of natural and synthetic biomarkers and various techniques for the early detection of CRC. An approach toward current advancement in CRC detection techniques and the role of NSAIDs in CRC chemoprevention has been explored systematically. Several prominent governing mechanisms of the anti-cancer effects of NSAIDs and their synergistic effect with statins for an effective chemopreventive measure have also been discussed in this review paper.

Facile synthesis of Pt catalysts functionalized porous ZnO nanowires with enhanced gas-sensing properties

Low working temperature and high sensitivity of gas sensors are critical in their practical applications; however, these properties are usually contradictory and cannot be realized simultaneously. Here, ZnO porous nanowires (PNWs) are prepared by a modified electrospinning method, and Pt nanoparticles (NPs) are doped on their surface by chemical reduction. The effects on morphology, specific surface area, and oxygen vacancy are discussed for the acetone gas-sensing performance. Results showed that Pt-ZnO PNWs responded optimally to acetone gas at 160 °C at 16.7–1.8 ppm, which was three-fold greater than that of pristine ZnO PNWs. In addition, the lowest detection limit is 50 ppb, a ten-fold lower level than pristine ZnO PNWs. The sensor exhibits superior acetone selectivity, humidity resistance, repeatability, long-time stability, noble metals, and a porous design with a large surface area, providing synergistic effects that increase the number of surface adsorption sites. Thus, the approach provided a new comprehension for loading a high-dispersibility catalyst onto the porous structure surface as a potential breath analyzer.

Computational fluid dynamic analysis of corona virus patients breathing in an airplane

Effective ventilation systems are essential to control the transmission of airborne aerosol particles, such as the SARS-CoV-2 virus in aircraft cabins, which is a significant concern for people commuting by airplane. Validated computational fluid dynamic models are frequently and effectively used to investigate air distribution and pollutant transport. In this study, the effectiveness of different ventilation systems with varying outlet vent locations were computationally compared to determine the best ventilation system for minimizing the risk of airborne transmission. The cabin air conditioning system was optimized to determine how design variables (air inlet temperature, outlet valve width and location, and mass flow rate) affect output parameters, including particle residence time, age of air, and thermal comfort conditions. Inlet mass flow rate was observed to be an influential variable impacting all output parameters, especially on age of air, where it was the most influential. In contrast, the least effective variable was width of the outlet valve, which only affected the particle residence time. Also, Predicted Mean Vote and Predicted Percentage Dissatisfied indices were the most affected by air inlet temperature, which had an inverse relation, while the outlet valve location had the greatest effect on particle residence time.

Druken alcohol intelligent detection system IoT based Arduino controller

An intelligent alcohol detection system has been created to recognize the location of drunken drivers to prevent such road incidents. The project is being enhanced to use the internet of things (IoT) to make it easier for users to track their location and receive messages through their smartphones. The alcohol breath analyzer sensor detects the amount of alcohol in the driver's breath and the liquid crystal display (LCD) will display "Alcohol Detected" and the blood alcohol concentration (BAC) value if the level exceeds the threshold. İn addition, the global system for mobile (GSM) will send short message service (SMS) or make phone calls and telegram will sends BAC value, while the GPS will broadcast the discovered alcohol's location. This project implicitly provides more benefits for current efforts in the development of accident prevention systems in the hopes of putting them into practice in the real world to improve road safety.

Noninvasive detection of soft tissue sarcoma using volatile organic compounds in exhaled breath: a pilot study.

Aim: The aim of this pilot study was to assess whether an electronic nose can detect patients with soft tissue sarcoma (STS) based on volatile organic compound profiles in exhaled breath. Patients & methods: In this cross-sectional pilot study, patients with primary STS and healthy controls, matched on sex and age, were included for breath analysis. Machine learning techniques were used to develop the best-fitting model. Results: Fifty-nine breath samples were collected (29 STS and 30 control) from March 2018 to March 2022. The final model yielded a c-statistic of 0.85 with a sensitivity of 83% and specificity of 60%. Conclusion: This study suggests that exhaled volatile organic compound analysis could serve as a noninvasive diagnostic biomarker for the detection of STS with a good performance.

Portable Breath-Based Volatile Organic Compound Monitoring for the Detection of COVID-19 During the Circulation of the SARS-CoV-2 Delta Variant and the Transition to the SARS-CoV-2 Omicron Variant

Breath analysis has been explored as a noninvasive means to detect COVID-19. However, the impact of emerging variants of SARS-CoV-2, such as Omicron, on the exhaled breath profile and diagnostic accuracy of breath analysis is unknown. To evaluate the diagnostic accuracies of breath analysis on detecting patients with COVID-19 when the SARS-CoV-2 Delta and Omicron variants were most prevalent. This diagnostic study included a cohort of patients who had positive and negative test results for COVID-19 using reverse transcriptase polymerase chain reaction between April 2021 and May 2022, which covers the period when the Delta variant was overtaken by Omicron as the major variant. Patients were enrolled through intensive care units and the emergency department at the University of Michigan Health System. Patient breath was analyzed with portable gas chromatography. Different sets of VOC biomarkers were identified that distinguished between COVID-19 (SARS-CoV-2 Delta and Omicron variants) and non-COVID-19 illness. Overall, 205 breath samples from 167 adult patients were analyzed. A total of 77 patients (mean [SD] age, 58.5 [16.1] years; 41 [53.2%] male patients; 13 [16.9%] Black and 59 [76.6%] White patients) had COVID-19, and 91 patients (mean [SD] age, 54.3 [17.1] years; 43 [47.3%] male patients; 11 [12.1%] Black and 76 [83.5%] White patients) had non-COVID-19 illness. Several patients were analyzed over multiple days. Among 94 positive samples, 41 samples were from patients in 2021 infected with the Delta or other variants, and 53 samples were from patients in 2022 infected with the Omicron variant, based on the State of Michigan and US Centers for Disease Control and Prevention surveillance data. Four VOC biomarkers were found to distinguish between COVID-19 (Delta and other 2021 variants) and non-COVID-19 illness with an accuracy of 94.7%. However, accuracy dropped substantially to 82.1% when these biomarkers were applied to the Omicron variant. Four new VOC biomarkers were found to distinguish the Omicron variant and non-COVID-19 illness (accuracy, 90.9%). Breath analysis distinguished Omicron from the earlier variants with an accuracy of 91.5% and COVID-19 (all SARS-CoV-2 variants) vs non-COVID-19 illness with 90.2% accuracy. The findings of this diagnostic study suggest that breath analysis has promise for COVID-19 detection. However, similar to rapid antigen testing, the emergence of new variants poses diagnostic challenges. The results of this study warrant additional evaluation on how to overcome these challenges to use breath analysis to improve the diagnosis and care of patients.

A Strategy to Enhance Humidity Robustness of p‐Type CuO Sensors for Breath Acetone Quantification

Low‐cost metal oxide sensors are highly attractive for emerging applications such as breath analysis. Particularly promising are p‐type sensors that can operate at low temperatures, a key requirement for compact and low‐power devices. To date, however, these sensors lack sufficient sensitivity, selectivity, and humidity robustness to fulfil stringent requirements faced in real applications. Herein, a flame‐made and low‐power sensor (operated at 150 °C) that consists of CeO2‐decorated CuO nanoparticles is introduced, as determined by X‐ray diffraction and X‐ray photoelectron spectroscopy analysis. Most remarkably, this sensor features excellent robustness to 10–90% relative humidity. This is attributed to the presence of CeO2 nanoclusters, which may act by scavenging OH− and allow the readsorption of oxygen onto the CuO surface. To demonstrate its immediate impact, this sensor is investigated for the detection of acetone, a biomarker for fat burning. It detects acetone with high sensitivity (i.e., 50 ppb) and features excellent acetone selectivity (>9.8) toward key inorganic interferants (i.e., NH3, H2, and CO). Most importantly, the CeO2–CuO sensor accurately quantifies acetone concentrations in the exhaled breath of 16 volunteers (bias and precision of 90 and 457 ppb). As a result, it is attractive for low‐power and humidity robust detection of volatiles in breath analysis.

철도안전법상 음주업무에 대한 몇 가지 문제점

The Railway Safety Act prohibits drinking and stipulates punishment for violations, but there are the following problems. First, the subject of this crime is the identity offender. Therefore, even if a railroad vehicle of an unidentified person is drunk driving or aiding and abetting, it cannot be punished, so it should be revised as a general offender. Therefore, it is considered reasonable to define it as a general offender in paragraph (1) and to have a ban on drunk driving of railway workers in paragraph (2). Second, if a railroad worker drinks more than a certain amount of alcohol, it is stipulated as the same legal type regardless of the blood alcohol concentration standard. However, it is necessary to subdivide and define the statutory sentence according to the blood alcohol concentration in accordance with the principle of responsibility. Third, breath testing is to investigate drinking work. However, there is a higher risk of refusing to comply with the drinking test as the statutory punishment for violating the drinking business is stipulated to be lower than non-compliance with the drinking test. Therefore, it is necessary to amend the statutory sentence for violations of drinking work and non-compliance with drinking tests to be the same. Fourth, regulations that allow railroad workers to arbitrarily revoke or suspend their driver's license or control qualification regardless of the recovery of drinking work or refusal to take breathalyzer tests are not appropriate. Therefore, from the second time of recidivism, that is, it is necessary to cancel or suspend the license or control qualification.

Using a Contemporary Portable Metabolic Gas Exchange System for Assessing Energy Expenditure: A Validity and Reliability Study.

There are several methods available to assess energy expenditure, all associated with inherent pros and cons that must be adequately considered for use in specific environments and populations. A requirement of all methods is that they must be valid and reliable in their capability to accurately measure oxygen consumption (VO2) and carbon dioxide production (VCO2). The purpose of this study was to evaluate the reliability and validity of the mobile CO2/O2 Breath and Respiration Analyzer (COBRA) relative to a criterion system (Parvomedics TrueOne 2400®, PARVO) with additional measurements to compare the COBRA to a portable system (Vyaire Medical, Oxycon Mobile®, OXY). Fourteen volunteers with a mean of 24 years old, body weight of 76 kg, and a VO2peak of 3.8 L∙min-1 performed four repeated trials of progressive exercises. Simultaneous steady-state measurements of VO2, VCO2, and minute ventilation (VE) by the COBRA/PARVO and OXY systems were conducted at rest, while walking (23-36% VO2peak), jogging (49-67% VO2peak), and running (60-76% VO2peak). Data collection was randomized by the order of system tested (COBRA/PARVO and OXY) and was standardized to maintain work intensity (rest to run) progression across study trials and days (two trials/day over two days). Systematic bias was examined to assess the accuracy of the COBRA to PARVO and OXY to PARVO across work intensities. Intra- and inter-unit variability were assessed with interclass correlation coefficients (ICC) and a 95% limit of agreement intervals. The COBRA and PARVO produced similar measures for VO2 (Bias ± SD, 0.01 ± 0.13 L·min-1; 95% LoA, (-0.24, 0.27 L·min-1); R2 = 0.982), VCO2 (0.06 ± 0.13 L·min-1; (-0.19, 0.31 L·min-1); R2 = 0.982), VE (2.07 ± 2.76 L·min-1; (-3.35, 7.49 L·min-1); R2 = 0.991) across work intensities. There was a linear bias across both the COBRA and OXY with increased work intensity. The coefficient of variation for the COBRA ranged from 7 to 9% across measures for VO2, VCO2, and VE. COBRA was reliable across measurements for VO2 (ICC = 0.825; 0.951), VCO2 (ICC = 0.785; 0.876), and VE (ICC = 0.857; 0.945) for intra-unit reliability, respectively. The COBRA is an accurate and reliable mobile system for measuring gas exchange at rest and across a range of work intensities.

Analysis of a Broad Range of Carbonyl Metabolites in Exhaled Breath by UHPLC-MS.

Analysis of volatile organic compounds (VOCs) in exhaled breath (EB) has shown great potential for disease detection including lung cancer, infectious respiratory diseases, and chronic obstructive pulmonary disease. Although many breath sample collection and analytical methods have been developed for breath analysis, analysis of metabolic VOCs in exhaled breath is still a challenge for clinical application. Many carbonyl compounds in exhaled breath are related to the metabolic processes of diseases. This work reports a method of ultrahigh-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-MS) for the analysis of a broad range of carbonyl metabolites in exhaled breath. Carbonyl compounds in the exhaled breath were captured by a fabricated silicon microreactor with a micropillar array coated with 2-(aminooxy)ethyl-N,N,N-trimethylammonium (ATM) triflate. A total of six subgroups consisting of saturated aldehydes and ketones, hydroxy-aldehydes, and hydroxy-ketones, unsaturated 2-alkenals, and 4-hydroxy-2-alkenals were identified in the exhaled breath. The combination of a silicon microreactor for the selective capture of carbonyl compounds with UHPLC-MS analysis may provide a quantitative method for the analysis of carbonyls to identify disease markers in exhaled breath.

Optimization of a Breath Analysis Methodology to Potentially Diagnose Transplanted Kidney Rejection: A Preclinic Study

Chronic kidney disease (CKD) may result in end-stage renal disorder and an increased mortality rate. Presently, kidney transplantation represents the only definitive treatment to restore normal life expectancy. Nevertheless, there is an elevated risk of organ rejection in the short–medium term after surgery. This preclinic study proposes the optimization of an innovative, fast, non-invasive, and cheap thermal desorption-gas chromatograph–mass spectrometry (TD-GC–MS) protocol, which provides simple monitoring of the respiratory profile of CKD-affected patients, before and during the first year after surgery, and aims to preemptively predict the rejection of the transplanted kidney. Twenty volatile organic compounds (VOCs), known as targets and, which are representative of the major classes of molecules discriminating between CKD-affected patients and healthy individuals, were selected from the literature, and employed to optimize the methodology. Calibration curves, linearity concentration ranges, the limit of detection (LOD), and the limit of quantification (LOQ) were estimated for the chosen molecules as well as the intraday and interday reproducibility of the method. The applicability of the TD-GC–MS developed approach was tested by analyzing the breath of healthy and pathological subjects using the ReCIVA® device. Sixty-seven molecules were identified, and between these, thirteen of the twenty selected compounds were quantified and were identified to have high prognostic values.

UHPLC-MS/MS-Based Identity Confirmation of Amino Acids Involved in Response to and Side Effects from Antiseizure Medications.

Real-time breath analysis using secondary electrospray ionization coupled with high-resolution mass spectrometry is a fast and noninvasive method to access the metabolic state of a person. However, it lacks the ability to unequivocally assign mass spectral features to compounds due to the absence of chromatographic separation. This can be overcomed by using exhaled breath condensate and conventional liquid chromatography-mass spectrometry (LC-MS) systems. In this study, to the best of our knowledge, we confirm for the first time the presence of six amino acids (GABA, Oxo-Pro, Asp, Gln, Glu, and Tyr) previously reported to be involved in response to and side effects from antiseizure medications in exhaled breath condensate and by extension in exhaled human breath. Raw data are publicly available at MetaboLights with the accession number MTBLS6760.

High Sensitive and Selective Cu-doped ZnO Thin film for No2 Sensing with Chemical Root Method

Copper Doped Zinc Oxide-Thin films are prepared by the Sol-Gel method and annealing at 400°C, For sol preparation, we prepare 2- different types of solution, one is zinc nitrate hexahydrate and the second is copper nitrate, that are deeply discussed in this paper. The thin size was varied by XRD, the detected (h k l) peaks are confirmed with 2θ values and the morphology was also studied by field emission scanning electron microscopy (FESEM), the Nano-bubbles and nano-balls was observed. Electrical properties and VI- Characteristics were also done, and getting highly sensitive Performing results, finally, the gas sensing characteristic was taken by chemiresistive process. And the Gas Sensing performance was done with closed chamber methods and the High sensitive and selective performance result have been shown. The sensing parameters such as electrical properties, and VI- characteristics, for gases, are also observed we shown the response time and recovery time, The S=Rg/Ra formula is used for calculate the response of the films. The best of lower gas detection limits, towards NO2 gas, and also finalize the selectivity and sensitivity performance of the thin film. The final result shown that ZnO thinfilm can act as NO2 sensor and breath analyzer, for diabetes.

Results of Analysis of Volatile Organic Compound (VOC) Measurements Using Breath Analyzer on Coronavirus Disease 2019 (COVID-19) Confirmed Patients with Healthy People

Background/aim: The analysis of VOCs through respiration has been used for biomarker analysis for the detection of novel coronaviruses and has found mainly six VOCs by breath analysis by GC-IMS are ethanol, octane, acetone, cluster mixture of acetone/butanone and methanol. Previous research found exhaled methanol concentrations were lower in COVID-19 patients. The aim of this study was to analyze differences in VOC concentration in Covid-19 patients with healthy people. Methods: This Case Control study used 93 confirmed case samples of Covid-19 and 42 healthy people. Demographic and clinical data taken from anamnesis and/or medical records. VOC’s data of respiratory track are taken through the exhalation air in a bag and analyzed with breath analyzer. Statistical analysis was conducted using Mann-Whitney test. Results: VOC compound measured include CO2, C7H8, CH2O, NH4, TVOC, NO2, PM1.0, CO, NH3, and Acetone. Analysis between Covid-19 patients and healthy people showed significant differences in all VOC components CO2 (p=0,000), C7H8 (p=0,000), CH2O (p=0,000), NH4 (p=0,001), TVOC (p=0,000), NO2 (p=0,000), PM1.0 (p=0,000), CO (p=0,000), NH3 (P=0,000), Acetone (p=001). Logistic regression analysis was obtained no meaningful influence on each component of the VOC with covid/healthy people conditions of patients with components CO2 (p=1,000), C7H8 (p=1,000), CH2O (p=0,999), NH4 (p=1,000), TVOC (p=1,000), NO2 (p=1,000), PM1.0 (p=0,999), CO (p=0,999), NH3 (P=0,999), Acetone (p=1,000). Conclusion: There is a significant difference between the VOC results of confirmed COVID 19 patients and healthy people Keywords: breath analyzer, coronaviruses, COVID-19, healthy people, volatile organic component

Design and implementation of humidity sensor based on carbon nitride modified with graphene quantum dots

Relative humidity (RH) is one of the most important factors that deserve intensive study because of its impact on many aspects of life. In this work humidity sensor based on carbon nitride / graphene quantum dots (g-C3N4/GQDs) nanocomposites have been developed. The structure, morphology and composition properties of the g-C3N4/GQDs were investigated and analyzed by XRD, HR-TEM, FTIR, UV–Vis, Raman, XPS and BET surface area. The average particle size of GQDs was estimated from XRD to be 5 nm and confirmed using HRTEM. The HRTEM images prove that the GQDs are attached to the external surface of the g-C3N4. The measured BET surface area was found to be 216 m2/g, 313 m2/g, and 545 m2/g for GQDs, g-C3N4, and g-C3N4/GQDs respectively. The d-spacing and crystallite size were estimated from XRD and HRTEM and found in a good matching. The humidity sensing behavior of g-C3N4/GQDs was measured in a wide span of humidity from 7% up to 97% RH under different testing frequencies. The obtained results demonstrate good reversibility and fast response/recovery time. The implemented sensor exhibits a great application prospect in humidity alarm devices, automatic diaper alarms, and breath analysis, which have advantages such as strong anti-interference capability, low cost, and easy to use.

Development of an analytical chip for colorimetric detection of medium-chain aldehydes by reaction with pararosaniline in porous glass

Medium-chain aldehydes are common human biogases that can be detected in the breath of patients with lung diseases. As such, the measurement of medium-chain aldehyde gases in human breath can provide significant, noninvasive, and diagnostic information related to the potential presence of such diseases. In this study, an analytical chip is developed for the detection of medium-chain aldehydes without interference from short-chain aldehydes. This analytical chip is composed of porous glass impregnated with pararosaniline and an acid (i.e., acetic acid with small amount of phosphoric acid). After exposure to medium-chain aldehydes, the red analytical chip became violet in color, and an absorption peak was observed at 620 nm. It was found that a non-reversible reaction occurred in the porous glass, therefore, the analytical chip functions in a cumulative manner. A linear relationship was determined between the absorbance change of the analytical chip at 620 nm and the nonanal exposure concentration. Importantly, the developed analytical chip successfully detected nonanal at concentrations of 8–270 ppb as calculated from the absorbance change at 620 nm after a 24 h exposure time. In addition, nonanal concentration was estimated using the change in the R value of the analytical chip photograph. This method is suitable for point-of-care breath analysis. Finally, the analytical chip was also found to be active toward octanal and decanal with a relative sensitivity of 0.7 compared to that of nonanal; it was not active toward short-chain aldehydes.

Calculations of adsorption-dependent refractive indices of metal-organic frameworks for gas sensing applications.

Detection of volatile organic compounds (VOCs) is one of the most challenging tasks in modelling breath analyzers because of their low concentrations (parts-per-billion (ppb) to parts-per-million (ppm)) in breath and the high humidity levels in exhaled breaths. The refractive index is one of the crucial optical properties of metal-organic frameworks (MOFs), which is changeable via the variation of gas species and concentrations that can be utilized as gas detectors. Herein, for the first time, we used Lorentz-Lorentz, Maxwell-Ga, and Bruggeman effective medium approximation (EMA) equations to compute the percentage change in the index of refraction (Δn%) of ZIF-7, ZIF-8, ZIF-90, MIL-101(Cr) and HKUST-1 upon exposure to ethanol at various partial pressures. We also determined the enhancement factors of the mentioned MOFs to assess the storage capability of MOFs and the biosensors' selectivity through guest-host interactions, especially, at low guest concentrations.

Assessment of an e-nose performance for the detection of COVID-19 specific biomarkers

Early, rapid and non-invasive diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is needed for the prevention and control of coronavirus disease 2019 (COVID-19). COVID-19 mainly affects the respiratory tract and lungs. Therefore, analysis of exhaled breath could be an alternative scalable method for reliable SARS-CoV-2 screening. In the current study, an experimental protocol using an electronic-nose (‘e-nose’) for attempting to identify a specific respiratory imprint in COVID-19 patients was optimized. Thus the analytical performances of the Cyranose®, a commercial e-nose device, were characterized under various controlled conditions. In addition, the effect of various experimental conditions on its sensor array response was assessed, including relative humidity, sampling time and flow rate, aiming to select the optimal parameters. A statistical data analysis was applied to e-nose sensor response using common statistical analysis algorithms in an attempt to demonstrate the possibility to detect the presence of low concentrations of spiked acetone and nonanal in the breath samples of a healthy volunteer. Cyranose® reveals a possible detection of low concentrations of these two compounds, in particular of 25 ppm nonanal, a possible marker of SARS-CoV-2 in the breath.

Crystal superlattices for versatile and sensitive quantum spectroscopy.

Nonlinear interferometers with quantum correlated photons have been demonstrated to improve optical characterization and metrology. These interferometers can be used in gas spectroscopy, which is of particular interest for monitoring greenhouse gas emissions, breath analysis and industrial applications. Here, we show that gas spectroscopy can be further enhanced via the deployment of crystal superlattices. This is a cascaded arrangement of nonlinear crystals forming interferometers, allowing the sensitivity to scale with the number of nonlinear elements. In particular, the enhanced sensitivity is observed via the maximum intensity of interference fringes that scales with low concentration of infrared absorbers, while for high concentration the sensitivity is better in interferometric visibility measurements. Thus, a superlattice acts as a versatile gas sensor since it can operate by measuring different observables, which are relevant to practical applications. We believe that our approach offers a compelling path towards further enhancements for quantum metrology and imaging using nonlinear interferometers with correlated photons.

LC-MS/MS Based Volatile Organic Compound Biomarkers Analysis for Early Detection of Lung Cancer

(1) Background: lung cancer is the world's deadliest cancer, but early diagnosis helps to improve the cure rate and thus reduce the mortality rate. Annual low-dose computed tomography (LD-CT) screening is an efficient lung cancer-screening program for a high-risk population. However, LD-CT has often been characterized by a higher degree of false-positive results. To meet these challenges, a volatolomic approach, in particular, the breath volatile organic compounds (VOCs) fingerprint analysis, has recently received increased attention for its application in early lung cancer screening thanks to its convenience, non-invasiveness, and being well tolerated by patients. (2) Methods: a LC-MS/MS-based volatolomics analysis was carried out according to P/N 5046800 standard based breath analysis of VOC as novel cancer biomarkers for distinguishing early-stage lung cancer from the healthy control group. The discriminatory accuracy of identified VOCs was assessed using subject work characterization and a random forest risk prediction model. (3) Results: the proposed technique has good performance compared with existing approaches, the differences between the exhaled VOCs of the early lung cancer patients before operation, three to seven days after the operation, as well as four to six weeks after operation under fasting and 1 h after the meal were compared with the healthy controls. The results showed that only 1 h after a meal, the concentration of seven VOCs, including 3-hydroxy-2-butanone (TG-4), glycolaldehyde (TG-7), 2-pentanone (TG-8), acrolein (TG-11), nonaldehyde (TG-19), decanal (TG-20), and crotonaldehyde (TG-22), differ significantly between lung cancer patients and control, with the invasive adenocarcinoma of the lung (IAC) having the most significant difference. (4) Conclusions: this novel, non-invasive approach can improve the detection rate of early lung cancer, and LC-MS/MS-based breath analysis could be a promising method for clinical application.