1,121 research outputs found

    Mass spectrometric analysis of volatile organic compounds in oesophago-gastric cancer

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    In the UK, oesophago-gastric (OG) cancer remains a disease with poor patient outcomes and only 35% of patients are suitable for potentially curative treatment at first presentation. Early detection of these cancers is necessary with Volatile Organic Compound (VOC) analysis being a promising area to explore for new endogenous biomarkers. In this research, the application of Selected-Ion Flow Tube Mass Spectrometry (SIFT-MS), a real-time technique, for the analysis of VOCs in biofluids and exhaled breath has been investigated. The primary aim of this research was to identify potential VOC biomarkers in oesophago-gastric cancer; the long-term application being the translational development of VOCs as non-invasive diagnostic tests. A total of 13 VOCs emitted from gastric content were investigated in the first study; acetone, formaldehyde, acetaldehyde, hexanoic acid, hydrogen sulphide, acetic acid, hydrogen cyanide and methyl phenol were found to be significantly different between oesophago-gastric cancer and healthy groups. In a study on the headspace of urine, acetaldehyde, acetone, acetic acid, hexanoic acid, hydrogen sulphide, methanol and phenol were found to be at significantly different concentrations between oesophago-gastric cancer, positive control and healthy groups. Methodology experiments including the optimisation of VOC sampling techniques with evaluation of exogenous contamination and variability measures have also been conducted. Investigation of reference ranges for C3-C10 aldehydes in healthy subjects using SIFT-MS have been undertaken for the first time; C4-C10 aldehydes were present in the exhaled breath of healthy persons at concentrations < 3 ppbv. In a study on 210 consecutive patients, increased concentrations of fatty acids, phenols and aldehydes were observed in the exhaled breath of patients with oesophageal and gastric adenocarcinoma. The potential effects of clinical confounding factors have been also assessed and possible explanations for the observed differences have been discussed. The results of the pilot study on acute infection demonstrated minimal influence on the cancer-linked VOCs in OG cancer, except for butanal. The analysis of gastric content, urine and exhaled breath have proven that trace compounds are more influential than abundant metabolites in upper gastro-intestinal malignancy. It is also demonstrated that VOC profiles rather than individual compounds are more accurate in the molecular-orientated diagnosis of oesophago-gastric cancer.Open Acces

    Applicability of non-invasively collected matrices for human biomonitoring

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    With its inclusion under Action 3 in the Environment and Health Action Plan 2004โ€“2010 of the European Commission, human biomonitoring is currently receiving an increasing amount of attention from the scientific community as a tool to better quantify human exposure to, and health effects of, environmental stressors. Despite the policy support, however, there are still several issues that restrict the routine application of human biomonitoring data in environmental health impact assessment. One of the main issues is the obvious need to routinely collect human samples for large-scale surveys. Particularly the collection of invasive samples from susceptible populations may suffer from ethical and practical limitations. Children, pregnant women, elderly, or chronically-ill people are among those that would benefit the most from non-invasive, repeated or routine sampling. Therefore, the use of non-invasively collected matrices for human biomonitoring should be promoted as an ethically appropriate, cost-efficient and toxicologically relevant alternative for many biomarkers that are currently determined in invasively collected matrices. This review illustrates that several non-invasively collected matrices are widely used that can be an valuable addition to, or alternative for, invasively collected matrices such as peripheral blood sampling. Moreover, a well-informed choice of matrix can provide an added value for human biomonitoring, as different non-invasively collected matrices can offer opportunities to study additional aspects of exposure to and effects from environmental contaminants, such as repeated sampling, historical overview of exposure, mother-child transfer of substances, or monitoring of substances with short biological half-lives

    Early Detection of Prostate Cancer: The Role of Scent

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    Prostate cancer (PCa) represents the cause of the second highest number of cancer-related deaths worldwide, and its clinical presentation can range from slow-growing to rapidly spreading metastatic disease. As the characteristics of most cases of PCa remains incompletely understood, it is crucial to identify new biomarkers that can aid in early detection. Despite the prostate-specific antigen serum (PSA) levels, prostate biopsy, and imaging representing the actual gold-standard for diagnosing PCa, analyzing volatile organic compounds (VOCs) has emerged as a promising new frontier. We and other authors have reported that highly trained dogs can recognize specific VOCs associated with PCa with high accuracy. However, using dogs in clinical practice has several limitations. To exploit the potential of VOCs, an electronic nose (eNose) that mimics the dog olfactory system and can potentially be used in clinical practice was designed. To explore the eNose as an alternative to dogs in diagnosing PCa, we conducted a systematic literature review and meta-analysis of available studies. PRISMA guidelines were used for the identification, screening, eligibility, and selection process. We included six studies that employed trained dogs and found that the pooled diagnostic sensitivity was 0.87 (95% CI 0.86โ€“0.89; I2, 98.6%), the diagnostic specificity was 0.83 (95% CI 0.80โ€“0.85; I2, 98.1%), and the area under the summary receiver operating characteristic curve (sROC) was 0.64 (standard error, 0.25). We also analyzed five studies that used an eNose to diagnose PCa and found that the pooled diagnostic sensitivity was 0.84 (95% CI, 0.80โ€“0.88; I2, 57.1%), the diagnostic specificity was 0.88 (95% CI, 0.84โ€“0.91; I2, 66%), and the area under the sROC was 0.93 (standard error, 0.03). These pooled results suggest that while highly trained dogs have the potentiality to diagnose PCa, the ability is primarily related to olfactory physiology and training methodology. The adoption of advanced analytical techniques, such as eNose, poses a significant challenge in the field of clinical practice due to their growing effectiveness. Nevertheless, the presence of limitations and the requirement for meticulous study design continue to present challenges when employing eNoses for the diagnosis of PCa

    Breathomicsโ€”exhaled volatile organic compound analysis to detect hepatic encephalopathy : a pilot study

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    he current diagnostic challenge with diagnosing hepatic encephalopathy (HE) is identifying those with minimal HE as opposed to the more clinically apparent covert/overt HE. Rifaximin, is an effective therapy but earlier identification and treatment of HE could prevent liver disease progression and hospitalization. Our pilot study aimed to analyse breath samples of patients with different HE grades, and controls, using a portable electronic (e) nose. 42 patients were enrolled; 22 with HE and 20 controls. Bedside breath samples were captured and analysed using an uvFAIMS machine (portable e-nose). West Haven criteria applied and MELD scores calculated. We classify HE patients from controls with a sensitivity and specificity of 0.88 (0.73-0.95) and 0.68 (0.51-0.81) respectively, AUROC 0.84 (0.75-0.93). Minimal HE was distinguishable from covert/overt HE with sensitivity of 0.79 and specificity of 0.5, AUROC 0.71 (0.57-0.84). This pilot study has highlighted the potential of breathomics to identify VOCs signatures in HE patients for diagnostic purposes. Importantly this was performed utilizing a non-invasive, portable bedside device and holds potential for future early HE diagnosis

    Advances in Electronic-Nose Technologies Developed for Biomedical Applications

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    The research and development of new electronic-nose applications in the biomedical field has accelerated at a phenomenal rate over the past 25 years. Many innovative e-nose technologies have provided solutions and applications to a wide variety of complex biomedical and healthcare problems. The purposes of this review are to present a comprehensive analysis of past and recent biomedical research findings and developments of electronic-nose sensor technologies, and to identify current and future potential e-nose applications that will continue to advance the effectiveness and efficiency of biomedical treatments and healthcare services for many years. An abundance of electronic-nose applications has been developed for a variety of healthcare sectors including diagnostics, immunology, pathology, patient recovery, pharmacology, physical therapy, physiology, preventative medicine, remote healthcare, and wound and graft healing. Specific biomedical e-nose applications range from uses in biochemical testing, blood-compatibility evaluations, disease diagnoses, and drug delivery to monitoring of metabolic levels, organ dysfunctions, and patient conditions through telemedicine. This paper summarizes the major electronic-nose technologies developed for healthcare and biomedical applications since the late 1980s when electronic aroma detection technologies were first recognized to be potentially useful in providing effective solutions to problems in the healthcare industry

    ์งˆ๋ณ‘ ๋ฐ”์ด์˜ค๋งˆ์ปค ๋ฐœ๊ตด ๋ฐ ๊ทธ์™€ ๊ฒฐํ•ฉํ•˜๋Š” ํ›„๊ฐ ์ˆ˜์šฉ์ฒด ํƒ์ƒ‰

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ํ™”ํ•™์ƒ๋ฌผ๊ณตํ•™๋ถ€, 2020. 8. ๋ฐ•ํƒœํ˜„.Due to the development of medical technology and systems, the premature mortality rate due to disease has decreased significantly compared to the past. However, lethality from some incurable diseases including cancer is still high. Because it is difficult to feel conscious symptoms before the disease develops to a late stage, and the existing diagnosis method is inaccessible due to the invasive method and cost of examination. Due to this reason, the latest disease diagnosis technology is developing in the direction of improving accessibility, and in particular, the need for non-invasive and economic method is emerging. As a typical example, the technology for diagnosing a disease by detecting a specific volatile organic compounds enables simple diagnosis without pain because it can detect the signal of disease from exhaled breath, sweat, urine, and saliva as well as blood and body fluids. In particular, the bioelectronic sensor has demonstrated excellent selectivity and sensitivity by combining a primary transducer such as an olfactory receptor with a secondary transducer containing a nanostructured semiconductor such as carbon nanotubes or graphene. The purposes of this research are identification of disease biomarkers and screening, performance evaluation of olfactory receptors for the detection of biomarkers that are essential for development of bioeletronic sensor. The selected diseases for study are lung cancer, tuberculosis, and gastric cancer. First, the discovery of biomarkers for lung cancer and the screening of human olfactory receptors were performed. The lung cancer cell line and the normal lung cell line were cultured to compare the composition of headspace gas by GC / MS, and volatile organic compound 2-ethyl-1-hexanol, which is more frequently generated in lung cancer cell lines, was identified. In addition, human olfactory receptors capable of detecting this biomarker were screened using a dual-glo luciferase reporter gene assay. It was confirmed that the identified olfactory receptor sensitively and selectively detects the lung cancer biomarker, and then conducted olfactory nanovesicle generation and performance evaluation for use as a primary transducer of the bioelectronic sensor in the further study. In the second study, the screening of human olfactory receptors were carried out for identification of olfactory receptor capable of detecting 5 tuberculosis biomarkers found in urine [95]. The screening was conducted by transfectng the human olfactory receptor genes and the luciferase reporter gene into the HEK293 cell line to confirm the responsivity to the tuberculosis biomarkers. As a result, olfactory receptors recognizing each tuberculosis biomarker were selected, and their responsivity and selectivity were also analyzed. Third, a number of exhaled breath samples of gastric cancer patients and healthy subjects were collected and analyzed using GC/MS. As a result, butyl acid and propionic acid, which are volatile organic compounds found in relatively large amounts in the exhaled breath of gastric cancer patients, were identified. In particular, solid-phase microextraction (SPME) fibers were used as a instruments of collecting and concentrating volatile organic compounds to completely analyze the biomarkers containing a very small amount in the exhaled breath samples. To improve the reliability of the selected volatile organic compounds as biomarkers, we build a diagnostic model that distinguishes patients based on the amount of biomarkers in the exhaled breath through statistical analysis of overall data, and their sensitivity and selectivity were calculated. In addition, in order to identify a primary transducer of a bioelectronic sensor that detects biomarkers included in exhaled breath, the responsivity and selectivity of 2 human olfactory receptors known to detect butyric acid and propionic acid were estimated. Development of disease diagnosis technology is an inevitable process for universal welfare and extension of life expectancy. Diagnostic methods targeting disease-specific volatile organic compounds are attracting attention in academia as a next-generation diagnostic technology, and are actively being studied all over the world. In this thesis, several disease-specific volatile organic compounds have been newly identified, and the human olfactory receptors capable of recognizing disease biomarkers were screened. The above research results are expected to be useful for the development of sensitive and selective bioelectronic sensor for disease diagnosis.์˜๋ฃŒ๊ธฐ์ˆ ๊ณผ ์ฒด๊ณ„์˜ ๋ฐœ๋‹ฌ๋กœ ์ธํ•ด ์งˆ๋ณ‘์œผ๋กœ ์ธํ•œ ์กฐ๊ธฐ ์‚ฌ๋ง๋ฅ ์€ ๊ณผ๊ฑฐ์— ๋น„ํ•ด ํฌ๊ฒŒ ์ค„์–ด๋“ค์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์•”์„ ๋น„๋กฏํ•œ ์ผ๋ถ€ ๋‚œ์น˜์„ฑ ์งˆ๋ณ‘์œผ๋กœ ์ธํ•œ ์น˜์‚ฌ์œจ์€ ์—ฌ์ „ํžˆ ๋†’์€ ํŽธ์ด๋‹ค, ์ด๋Š” ์งˆ๋ณ‘์ด ์น˜๋ช…์ ์ธ ์ˆ˜์ค€๊นŒ์ง€ ๋ฐœ๋‹ฌํ•˜๊ธฐ ์ „์— ์ž๊ฐ์ฆ์ƒ์„ ๋Š๋ผ๊ธฐ ํž˜๋“ค๋‹ค๋Š” ์ ๊ณผ ๊ธฐ์กด์˜ ๊ฒ€์ง„ ๋ฐฉ๋ฒ•์ด ํŠน์œ ์˜ ์นจ์Šต์ ์ธ ๋ฐฉ์‹๊ณผ ๊ฒ€์‚ฌ ๋น„์šฉ ๋•Œ๋ฌธ์— ์ ‘๊ทผ์„ฑ์ด ๋–จ์–ด์ง„๋‹ค๋Š” ์ ์—์„œ ๋น„๋กฏ๋œ๋‹ค. ์ด๋Ÿฐ ์—ฐ์œ ๋กœ ์ตœ์‹  ์งˆ๋ณ‘ ์ง„๋‹จ ๊ธฐ์ˆ ์€ ์ ‘๊ทผ์„ฑ์˜ ํ–ฅ์ƒ์„ ์ถ”๊ตฌํ•˜๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ๋ฐœ์ „ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ํŠนํžˆ ๋น„ ์นจ์Šต์ ์ด๊ณ  ๊ฒฝ์ œ์ ์ธ ๋ฐฉ๋ฒ•์˜ ํ•„์š”์„ฑ์ด ๋Œ€๋‘๋˜๊ณ  ์žˆ๋‹ค. ๋Œ€ํ‘œ์ ์ธ ์˜ˆ์‹œ๋กœ, ํŠน์ด์ ์ธ ํœ˜๋ฐœ์„ฑ ์œ ๊ธฐ๋ฌผ์งˆ์„ ๊ฐ์ง€ํ•˜์—ฌ ์งˆ๋ณ‘์„ ์ง„๋‹จํ•˜๋Š” ๊ธฐ์ˆ ์€ ํ”ผ๋‚˜ ์ฒด์•ก ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋‚ ์ˆจ, ๋•€, ์†Œ๋ณ€, ์นจ ๋“ฑ์„ ๋งค๊ฐœ๋กœ ์™€๋ณ‘ ์—ฌ๋ถ€๋ฅผ ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ๊ธฐ์— ๊ณ ํ†ต์ด ์ˆ˜๋ฐ˜๋˜์ง€ ์•Š๋Š” ๊ฐ„๋‹จํ•œ ์ง„๋‹จ์„ ๊ฐ€๋Šฅ์ผ€ ํ•œ๋‹ค. ํŠนํžˆ, ๋ฐ”์ด์˜ค ์ „์ž ์„ผ์„œ๋Š” ์นด๋ณธ๋‚˜๋…ธํŠœ๋ธŒ๋‚˜ ๊ทธ๋ผํ•€ ๊ฐ™์€ ๋‚˜๋…ธ ๊ตฌ์กฐ ๋ฐ˜๋„์ฒด๋ฅผ ํฌํ•จํ•œ 2์ฐจ ๋ณ€ํ™˜๊ธฐ์— ํ›„๊ฐ ์ˆ˜์šฉ์ฒด์™€ ๊ฐ™์€ 1์ฐจ ๋ณ€ํ™˜๊ธฐ๋ฅผ ๊ฒฐํ•ฉํ•˜์—ฌ ์šฐ์ˆ˜ํ•œ ์„ ํƒ๋„์™€ ๋ฏผ๊ฐ๋„๋ฅผ ์„ ๋ณด์ธ ๋ฐ” ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ์งˆ๋ณ‘ ์ง„๋‹จ์šฉ ๋ฐ”์ด์˜ค ์ „์ž ์„ผ์„œ ์ œ์ž‘์„ ์œ„ํ•ด ํ•„์ˆ˜์ ์œผ๋กœ ์ด๋ฃจ์–ด์ ธ์•ผ ํ•˜๋Š” ์งˆ๋ณ‘ ํ‘œ์ง€๋ฌผ์งˆ ์„ ์ •๊ณผ, ํ‘œ์ง€๋ฌผ์งˆ ํƒ์ง€๋ฅผ ์œ„ํ•œ ํ›„๊ฐ ์ˆ˜์šฉ์ฒด ๋ฐœ๊ตด ๋ฐ ์„ฑ๋Šฅ ํ‰๊ฐ€์ด๋‹ค. ์—ฐ๊ตฌ ๋Œ€์ƒ์œผ๋กœ ์„ ํƒํ•œ ์งˆ๋ณ‘์€ ํ์•”, ๊ฒฐํ•ต, ๊ทธ๋ฆฌ๊ณ  ์œ„์•”์ด๋‹ค. ๋จผ์ € ํ์•”์˜ ํ‘œ์ง€๋ฌผ์งˆ ๋ฐœ๊ตด๊ณผ ์ธ๊ฐ„ ํ›„๊ฐ ์ˆ˜์šฉ์ฒด ํƒ์ƒ‰์ด ์ˆ˜ํ–‰๋˜์—ˆ๋‹ค. ํ์•” ์„ธํฌ์ฃผ์™€ ์ •์ƒ ํ ์„ธํฌ์ฃผ๋ฅผ ๋ฐฐ์–‘ํ•˜์—ฌ ๋‘๋ถ€๊ณต๊ฐ„์˜ ๊ฐ€์Šค ์กฐ์„ฑ์„ GC/MS๋กœ ๋น„๊ตํ•˜์˜€๊ณ , ํ์•” ์„ธํฌ์—์„œ ๋” ๋งŽ์ด ๋ฐœ์ƒํ•˜๋Š” ํœ˜๋ฐœ์„ฑ ์œ ๊ธฐ๋ฌผ์งˆ 2-์—ํ‹ธํ—ฅ์‚ฐ์˜ฌ์„ ํŠน์ •ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด ๋ฌผ์งˆ์„ ๊ฐ์ง€ํ•  ์ˆ˜ ์žˆ๋Š” ์ธ๊ฐ„ ํ›„๊ฐ ์ˆ˜์šฉ์ฒด๋ฅผ ์ด์ค‘๋ฐœ๊ด‘ ๋ฃจ์‹œํผ๋ ˆ์ด์ฆˆ ๊ฒ€์ •๋ฒ•์„ ์ด์šฉํ•˜์—ฌ ํƒ์ƒ‰ํ•˜์˜€๋‹ค. ๋ฐœ๊ตด๋œ ํ›„๊ฐ ์ˆ˜์šฉ์ฒด๊ฐ€ ํ์•” ํ‘œ์ง€๋ฌผ์งˆ์„ ๋ฏผ๊ฐํ•˜๊ณ  ์„ ํƒ์ ์œผ๋กœ ๊ฐ์ง€ํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ, ํ–ฅํ›„ ๋ฐ”์ด์˜ค ์ „์ž ์„ผ์„œ์˜ 1์ฐจ ์†Œ์ž๋กœ ์‚ฌ์šฉํ•˜๊ธฐ ์œ„ํ•œ ํ›„๊ฐ ๋‚˜๋…ธ๋ฒ ์‹œํด ์ƒ์‚ฐ ๋ฐ ์„ฑ๋Šฅ ํ‰๊ฐ€๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๋‘ ๋ฒˆ์งธ ์—ฐ๊ตฌ์—์„œ๋Š” ์†Œ๋ณ€์—์„œ ๋ฐœ๊ฒฌ๋œ ๊ฒฐํ•ต ๊ด€๋ จ 5์ข…์˜ ํœ˜๋ฐœ์„ฑ ์œ ๊ธฐ๋ฌผ์งˆ๋“ค์„ ๊ฐ์ง€ํ•  ์ˆ˜ ์žˆ๋Š” ์ธ๊ฐ„ ํ›„๊ฐ ์ˆ˜์šฉ์ฒด๋ฅผ ํƒ์ƒ‰ํ•˜์˜€๋‹ค. ํƒ์ƒ‰ ๊ณผ์ •์€ HEK293 ์„ธํฌ์ฃผ์— ์ธ๊ฐ„ ํ›„๊ฐ ์ˆ˜์šฉ์ฒด ์œ ์ „์ž์™€ ๋ฃจ์‹œํผ๋ ˆ์ด์ฆˆ ๋ฆฌํฌํ„ฐ ์œ ์ „์ž๋ฅผ ํ˜•์งˆ๋„์ž…ํ•˜์—ฌ ๊ฒฐํ•ต ๋ฐ”์ด์˜ค๋งˆ์ปค๋“ค์— ๋Œ€ํ•œ ๋ฐ˜์‘์„ฑ์„ ํ™•์ธํ•จ์œผ๋กœ์จ ์ง„ํ–‰๋˜์—ˆ๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ ๊ฐ๊ฐ์˜ ๊ฒฐํ•ต ๋ฐ”์ด์˜ค๋งˆ์ปค์— ๋Œ€ํ•œ ํ›„๊ฐ ์ˆ˜์šฉ์ฒด๊ฐ€ ์„ ์ •๋˜์—ˆ์œผ๋ฉฐ, ๊ทธ ๋ฐ˜์‘์„ฑ๊ณผ ์„ ํƒ๋„ ๋˜ํ•œ ๋ถ„์„๋˜์—ˆ๋‹ค. ์„ธ๋ฒˆ์งธ๋กœ, ์œ„์•” ํ™˜์ž์™€ ๊ฑด๊ฐ•ํ•œ ์‚ฌ๋žŒ์˜ ๋‚ ์ˆจ ์ƒ˜ํ”Œ์„ ๋‹ค์ˆ˜ ์ฑ„์ทจํ•˜์—ฌ GC/MS ์žฅ๋น„๋ฅผ ์ด์šฉํ•ด ๋ถ„์„ํ•˜๊ณ  ๋น„๊ตํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ์œ„์•” ํ™˜์ž์—๊ฒŒ์„œ ์ƒ๋Œ€์ ์œผ๋กœ ๋งŽ์ด ๋ฐœ๊ฒฌ๋˜๋Š” ํœ˜๋ฐœ์„ฑ ์œ ๊ธฐ๋ฌผ์งˆ์ธ ๋ทฐํ‹ธ์‚ฐ๊ณผ ํ”„๋กœํ”ผ์˜จ์‚ฐ์„ ํŠน์ •ํ•˜์˜€๋‹ค. ํŠนํžˆ, ๋‚ ์ˆจ ์ƒ˜ํ”Œ ๋‚ด์— ๋งค์šฐ ์ ์€ ์–‘์ด ํฌํ•จ๋œ ํ‘œ์ง€๋ฌผ์งˆ์„ ๋น ์ง์—†์ด ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ํœ˜๋ฐœ์„ฑ ์œ ๊ธฐ๋ฌผ์งˆ ์ฑ„์ทจ ๋ฐ ๋†์ถ• ์ˆ˜๋‹จ์œผ๋กœ ๊ณ ์ฒด ๋ฏธ์„ธ์ถ”์ถœ (SPME) ์„ฌ์œ ๋ฅผ ํ™œ์šฉํ•˜์˜€๋‹ค. ์„ ์ •ํ•œ ํœ˜๋ฐœ์„ฑ ์œ ๊ธฐ๋ฌผ์งˆ์˜ ํ‘œ์ง€๋ฌผ์งˆ๋กœ์„œ์˜ ์‹ ๋ขฐ๋„๋ฅผ ์ œ๊ณ ํ•˜๊ธฐ ์œ„ํ•ด, ์ „์ฒด ์ž๋ฃŒ์˜ ํ†ต๊ณ„ ๋ถ„์„ ๊ณผ์ •์„ ํ†ตํ•ด ๋‚ ์ˆจ ๋‚ด์˜ ํ‘œ์ง€๋ฌผ์งˆ ํฌํ•จ๋Ÿ‰์„ ๊ธฐ์ค€์œผ๋กœ ํ™˜์ž ์—ฌ๋ถ€๋ฅผ ๊ตฌ๋ถ„์ง“๋Š” ์ง„๋‹จ ๋ชจ๋ธ์„ ๊ตฌ์ถ•ํ•˜๊ณ  ๊ทธ ๋ฏผ๊ฐ๋„์™€ ์„ ํƒ๋„๋ฅผ ์‚ฐ์ถœํ•˜์˜€๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ, ํ–ฅํ›„ ์ง„ํ–‰ํ•  ๋‚ ์ˆจ์„ ๋Œ€์ƒ์œผ๋กœ ํ•œ ์œ„์•” ์ง„๋‹จ์šฉ ๋ฐ”์ด์˜ค ์ „์ž ์„ผ์„œ ์ œ์ž‘์„ ์œ„ํ•ด, ๋ทฐํ‹ธ์‚ฐ๊ณผ ํ”„๋กœํ”ผ์˜จ์‚ฐ์„ ๊ฐ์ง€ํ•œ๋‹ค๊ณ  ์•Œ๋ ค์ง„ ์ธ๊ฐ„ ํ›„๊ฐ ์ˆ˜์šฉ์ฒด 2์ข…์˜ ๋ฐ˜์‘์„ฑ๊ณผ ์„ ํƒ๋„๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ์งˆ๋ณ‘ ์ง„๋‹จ๊ธฐ์ˆ  ๊ฐœ๋ฐœ์€ ์ธ๋ฅ˜์˜ ๋ณดํŽธ์  ๋ณต์ง€์™€ ํ‰๊ท ์ˆ˜๋ช… ์—ฐ์žฅ์„ ์œ„ํ•˜์—ฌ ํ•„์—ฐ์ ์œผ๋กœ ์ด๋ฃจ์–ด์ ธ์•ผ ํ•˜๋Š” ๊ณผ์ •์ด๋‹ค. ์งˆ๋ณ‘ ํŠน์ด์  ํœ˜๋ฐœ์„ฑ ์œ ๊ธฐ๋ฌผ์งˆ์„ ๋Œ€์ƒ์œผ๋กœ ์‚ผ๋Š” ์ง„๋‹จ ๋ฐฉ์‹์€ ์ฐจ์„ธ๋Œ€ ์ง„๋‹จ๊ธฐ์ˆ ๋กœ์จ ํ•™๊ณ„์—์„œ ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ์œผ๋ฉฐ, ์„ธ๊ณ„ ๊ฐ์ง€์—์„œ ํ™œ๋ฐœํ•˜๊ฒŒ ์—ฐ๊ตฌ๋˜๊ณ  ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋ช‡ ๊ฐ€์ง€ ์งˆ๋ณ‘ ํŠน์ด์  ํœ˜๋ฐœ์„ฑ ์œ ๊ธฐ๋ฌผ์งˆ์ด ์‹ ๊ทœ ๋ฐœ๊ตด๋˜์—ˆ์œผ๋ฉฐ, ๋˜ํ•œ ๊ธฐ์กด์— ์•Œ๋ ค์ง„ ์งˆ๋ณ‘ ํ‘œ์ง€๋ฌผ์งˆ์„ ๊ฐ์ง€ํ•˜๋Š” ๋Šฅ๋ ฅ์„ ๊ฐ€์ง„ ํ›„๊ฐ ์ˆ˜์šฉ์ฒด๋ฅผ ํƒ์ƒ‰ํ•˜๊ณ  ๊ทธ ๊ธฐ๋Šฅ์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ƒ์ˆ ํ•œ ์—ฐ๊ตฌ ์„ฑ๊ณผ๋“ค์ด ๋ฏผ๊ฐํ•˜๊ณ  ์„ ํƒ์ ์ธ ์งˆ๋ณ‘ ์ง„๋‹จ์šฉ ์ƒ์ฒด ์†Œ์ž ๊ฐœ๋ฐœ์— ์œ ์šฉํ•˜๊ฒŒ ํ™œ์šฉ๋˜๊ธธ ๊ธฐ๋Œ€ํ•œ๋‹ค.Chapter 1. Research Background and Objectives 1 Chapter 2. Literature Review 4 2.1 Volatolomics 5 2.2 Biomarkers of disease 6 2.2.1 Volatile organic compounds related to disease 6 2.2.2 Sources and biochemical pathways of disease-related volatile organic compounds 7 2.3 Deorphanization and application of olfactory receptors 9 Chapter 3. Experimental Procedures 11 3.1 Collection and analysis of headspace gas from cell lines 12 3.1.1 Cell culture and headspace gas sampling 12 3.1.2 Headspace gas analysis with GC/MS 15 3.2 Identification of gastric cancer biomarkers from breath 17 3.2.1 Study groups and collection of clinical data 17 3.2.2 Sampling of exhaled breath and environmental gas 19 3.2.3 SPME-GC/MS analysis 19 3.2.4 Statistical analysis 20 3.3 Gene cloning 21 3.4 Production of olfactory receptor proteins 22 3.4.1 Expression of olfactory receptors in mammalian cells 22 3.4.2 Generation of olfactory nanovesicles 23 3.5 Characterization of olfactory receptor proteins 25 3.5.1 Immunocytochemistry 25 3.5.2 Western blot analysis 25 3.5.3 Calcium signaling assay 25 3.5.4 Dual-glo luciferase assay 28 Chapter 4. Identification of lung cancer biomarkers using a cancer cell line and screening of olfactory receptors for the biomarker detection 29 4.1 Introduction 30 4.2 Collection and analysis of headspace gas of lung cancer cell line 32 4.3 Screening of human olfactory receptors recognizing 2-ethyl-1-hexanol 37 4.4 Generation and characterization of olfactory nanovesicles 39 4.5 Conclusions 41 Chapter 5. Screening of human olfactory receptors to detect tuberculosis-specific volatile organic compounds in urine 42 5.1 Introduction 43 5.2 Screening of human olfactory receptors 45 5.3 Characterization of olfactory receptors recognizing biomarkers of tuberculosis 51 5.5 Conclusions 54 Chapter 6 Identification and validation of gastric cancer biomarkers and assessment of human olfactory receptors for the biomarker detection 55 6.1 Introduction 56 6.2 Selection of SPME fiber type 58 6.3 Sampling and Analysis of Exhaled Breath 60 6.4 Changes in the amounts of VOCs in the breath of gastric cancer patients before and after surgery 65 6.5 Statistical analysis for construction of diagnostic model 70 6.6 Cell-based assay for characterization of human olfactory receptors recognizing gastric cancer biomarkers 74 6.7 Conclusions 77 Chapter 7. Overall Discussion and further suggestions 78 References 84 Appendix 1. Comparative evaluation of sensitivity to hexanal between human and canine olfactory receptors 102 A1.1 Abstract 103 A1.2 Introduction 103 A1.3 Cloning of hOR2W1 and cfOR0312 genes 105 A1.4 Expression of human and canine olfactory receptors on HEK293 cell surface 107 A1.5 Comparison of human and canine OR sensitivity to hexanal 109 A1.6 Conclusions 113 References 114 Abstract 118Docto

    Cell culture metabolomics in the diagnosis of lung cancer - The influence of cell culture conditions

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    Lung cancer is the leading cause of cancer deaths. Unfortunately, lung cancer is often diagnosed only when it becomes symptomatic or at an advanced stage when few treatment options are available. Hence, a diagnostic test suitable for screening widespread populations is required to enable earlier diagnosis. Analysis of exhaled breath provides a non-invasive method for early detection of lung cancer. Analysis of volatile organic compounds (VOCs) by various mass spectral techniques has identified potential biomarkers of disease. Nevertheless, the metabolic origins and the disease specificity of VOCs need further elucidation. Cell culture metabolomics can be used as a bottom-up approach to identify biomarkers of pathological conditions and can also be used to study the metabolic pathways that produce such compounds. This paper summarizes the current knowledge of lung cancer biomarkers in exhaled breath and emphasizes the critical role of cell culture conditions in determining the VOCs produced in vitro. Hypoxic culture conditions more closely mimic the conditions of cancer cell growth in vivo. We propose that since hypoxia influences cell metabolism and so potentially the VOCs that the cancer cells produce, the cell culture metabolomics projects should consider culturing cancer cells in hypoxic conditions

    Volatile organic compounds in breath can serve as a non-invasive diagnostic biomarker for the detection of advanced adenomas and colorectal cancer

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    Contains fulltext : 220031.pdf (Publisherโ€™s version ) (Open Access)BACKGROUND: Colorectal cancer (CRC) is the third most common cancer diagnosis in the Western world. AIM: To evaluate exhaled volatile organic compounds (VOCs) as a non-invasive biomarker for the detection of CRC and precursor lesions using an electronic nose. METHODS: In this multicentre study adult colonoscopy patients, without inflammatory bowel disease or (previous) malignancy, were invited for breath analysis. Two-thirds of the breath tests were randomly assigned to develop training models which were used to predict the diagnosis of the remaining patients (external validation). In the end, all data were used to develop final-disease models to further improve the discriminatory power of the algorithms. RESULTS: Five hundred and eleven breath samples were collected. Sixty-four patients were excluded due to an inadequate breath test (nย =ย 51), incomplete colonoscopy (nย =ย 8) or colitis (nย =ย 5). Classification was based on the most advanced lesion found; CRC (nย =ย 70), advanced adenomas (AAs) (nย =ย 117), non-advanced adenoma (nย =ย 117), hyperplastic polyp (nย =ย 15), normal colonoscopy (nย =ย 125). Training models for CRC and AAs had an area under the curve (AUC) of 0.76 and 0.71 and blind validation resulted in an AUC of 0.74 and 0.61 respectively. Final models for CRC and AAs yielded an AUC of 0.84 (sensitivity 95% and specificity 64%) and 0.73 (sensitivity and specificity 79% and 59%) respectively. CONCLUSIONS: This study suggests that exhaled VOCs could potentially serve as a non-invasive biomarker for the detection of CRC and AAs. Future studies including more patients could further improve the discriminatory potential of VOC analysis for the detection of (pre-)malignant colorectal lesions. (https://clinicaltrials.gov Identifier NCT03488537)
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