Technologies for Clinical Diagnosis Using Expired Human Breath Analysis

Mathew, Thalakkotur Lazar; Pownraj, Prabhahari; Abdulla, Sukhananazerin; Pullithadathil, Biji

doi:10.3390/diagnostics5010027

Cited by 115 publications

(98 citation statements)

References 147 publications

(156 reference statements)

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“…Different analytical platforms can be used for analysis of the breath VOC pattern. Spectrometric technologies (gas chromatography‐mass spectrometry (GC‐MS) as gold standard, selected‐ion flow‐tube mass spectrometry (SIFT‐MS), differential mass spectrometry (DMS), roton‐transfer‐reaction mass spectrometry (PTR‐MS)/proton transfer reaction time‐of‐flight mass spectrometry (PTR‐TOFMS), high‐field asymmetric waveform ion mobility spectrometry (FAIMS)) are sophisticated instrumental tools offering many advantages in terms of selectivity and sensitivity, but they are inexpensive, time consuming and cannot be easily miniaturized (Mathew, Pownraj, Abdua, & Pullithadathil, ; García, Morales, Martín, Vilches, & Toledano, ; Rattray, Hamrang, Trivedi, Goodacre, & Fowler, ). Instead e‐noses are portable analytical platforms that provide a potential, relatively cheap and easy devices for breath analysis (García, Morales, & Toledano, ; Bikov, Lazar, & Horvath, ).…”

Section: Introductionmentioning

confidence: 99%

Chromatographic analysis of VOC patterns in exhaled breath from smokers and nonsmokers

Capone

Tufariello

Forleo

et al. 2017

Biomedical Chromatography

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Cigarette smoking harms nearly every organ of the body and causes many diseases. The analysis of exhaled breath for exogenous and endogenous volatile organic compounds (VOCs) can provide fundamental information on active smoking and insight into the health damage that smoke is creating. Various exhaled VOCs have been reported as typical of smoking habit and recent tobacco consumption, but to date, no eligible biomarkers have been identified. Aiming to identify such potential biomarkers, in this pilot study we analyzed the chemical patterns of exhaled breath from 26 volunteers divided into groups of nonsmokers and subgroups of smokers sampled at different periods of withdrawal from smoking. Solid-phase microextraction technique and gas chromatography/mass spectrometry methods were applied. Many breath VOCs were identified and quantified in very low concentrations (ppbv range), but only a few (toluene, pyridine, pyrrole, benzene, 2-butanone, 2-pentanone and 1-methyldecyclamine) were found to be statistically significant variables by Mann-Whitney test. In our analysis, we did not consider the predictive power of individual VOCs, as well as the criterion of uniqueness for biomarkers suggests, but we used the patterns of the only statistically significant compounds. Probit prediction model based on statistical relevant VOCs-patterns showed that assessment of smoking status is heavily time dependent. In a two-class classifier model, it is possible to predict with high specificity and sensitivity if a subject is a smoker who respected 1 hour of abstinence from smoking (short-term exposure to tobacco) or a smoker (labelled "blank smoker") after a night out of smoking (long-term exposure to tobacco). On the other side, in our study "blank smokers" are more like non-smokers so that the two classes cannot be well distinguished and the corresponding prediction results showed a good sensitivity but low selectivity.

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Section: Introductionmentioning

confidence: 99%

Chromatographic analysis of VOC patterns in exhaled breath from smokers and nonsmokers

Capone

Tufariello

Forleo

et al. 2017

Biomedical Chromatography

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“…Within this framework, analysis of VOCs in exhaled breath samples has been investigated for cancer diagnosis and patient stratification for personalised anticancer therapy . However, high inter‐individual variability as well as inter‐laboratory disparities for sample preparation and analysis represent major hurdles that still limit the use of volatolomics in clinics. Here, we demonstrate that healthy and tumour‐bearing mice can be discriminated without ambiguity by detecting a single airborne‐released exogenous VOC generated selectively in malignant tissues by the activation of a VOC‐based probe in response to a tumour‐specific stimulus.…”

Section: Figurementioning

confidence: 99%

Volatile Organic Compound Based Probe for Induced Volatolomics of Cancers

et al. 2019

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The development of efficient protocols for cancer diagnosis remains highly challenging. An emerging approach relies on the detection in exhaled breath of volatile organic compounds (VOC) produced by tumours.I nt his context, described here is anovel strategy in whichaVOC-based probe is converted selectively in malignant tissues,b yatumourassociated enzyme,for releasing the corresponding VOC. The latter is then detected in the exhaled breath as atumour marker for cancer diagnosis.T his approach allows the detection of several different tumours in mice,t he monitoring of tumour growth and tumour response to chemotherapy. Thus,t he concept of "induced volatolomics" provides an ew way to explore biological processes using VOC-based probes that could be adapted to many biomedical applications.

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“…Berdasarkan Mathew (2015) [10] mengenai diagnosis klinis menggunakan analisis ekspirasi pernapasan manusia, diketahui bahwa kandungan amonia orang sehat sebesar 0,5 -2 ppm [10]. Data yang diperoleh untuk gas amonia relawan perokok terlihat bahwa konsentrasi amonia yang diperoleh termasuk dalam kategori orang sehat.…”

Section: Hasil Pengukuran Konsentrasi Sampel Nafas Relawan Rokokunclassified

Kinerja Spektrometer Fotoakustik Laser CO2 untuk Deteksi Gas Etilen (C2H4), Aseton (C3H6O), Amonia (NH3) pada Gas Hembus Perokok

2017

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Kinerja spektrometer fotoakustik (SFA) telah dilakukan optimasi dan diaplikasikan. Karakterisasi SFA laser CO2 meliputi pemayaran garis laser CO2 dan garis serapan, penentuan kurva resonansi dan faktor kualitas, pengukuran noise sehingga diperoleh untuk faktor kualitas sebesar (14,5 + 0,6), (14,8 + 0,7), dan (14,2 + 0,6) dan batas deteksi terendah untuk gas etilen, aseton, amonia pada garis 10P14, 10P20, 10R14 yaitu (57,1 + 0,4) ppb, (63,8 + 2,4) ppb, dan (81,1 + 0,6) ppb. Selanjutnya SFA digunakan untuk mengukur konsentrasi gas etilen, aseton, amonia pada gas hembus perokok. Hasil pengukuran diolah menggunakan analisis multikomponen dan diperoleh konsentrasi rata-rata gas etilen, aseton, amonia pada gas hembus perokok tertinggi sebesar 1,303 ppm, 0,924 ppm, dan 1,753 ppm. Pada kondisi sebelum merokok diperoleh konsentrasi rata-rata gas etilen, aseton, amonia sebesar 0,873 ppm, 0,286 ppm, dan 1,137 ppm dan pada kondisi satu jam setelah merokok, konsentrasi gas hembus perokok diperoleh konsentrasi rata-rata gas etilen, aseton, amonia sebesar 0,901 ppm, 0,305 ppm, dan 1,176 ppm. Berdasarkan penelitian yang telah dilakukan ditemukan pola yang cukup identik yang ditunjukkan untuk ketiga jenis gas yaitu setelah 60 menit relawan merokok maka konsentrasi akhir gas etilen, aseton dan amonia akan sama dengan konsentrasi awalnya sebelum relawan merokok.kata kunci: Spektrometer Fotoakustik Laser CO2; perokok; analisis multikomponen

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Technologies for Clinical Diagnosis Using Expired Human Breath Analysis

Cited by 115 publications

References 147 publications

Chromatographic analysis of VOC patterns in exhaled breath from smokers and nonsmokers

Chromatographic analysis of VOC patterns in exhaled breath from smokers and nonsmokers

Volatile Organic Compound Based Probe for Induced Volatolomics of Cancers

Kinerja Spektrometer Fotoakustik Laser CO2 untuk Deteksi Gas Etilen (C2H4), Aseton (C3H6O), Amonia (NH3) pada Gas Hembus Perokok

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