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State of the Art in Breath Analysis for Disease Diagnosis...
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State of the Art in Breath Analysis for Disease Diagnosis and Exposure Assessment: Challenges and Solutions

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Analytical Chemistry".

Deadline for manuscript submissions: closed (15 October 2022) | Viewed by 5273

Special Issue Editor

Dr. Andreas Tsakalof

E-Mail Website
Guest Editor
Laboratory of Biochemistry, Faculty of Health Sciences, School of Medicine, University of Thessaly, Biopolis, 41111 Larissa, Greece
Interests: chemical measurement science; material science; pharmacy; clinical diagnostics; molecular medicine and biomedicine
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Breath analysis has great potential to offer non-invasive diagnostic tests for preventive screening and early detection of disease, monitoring the effectiveness of proposed therapies or assessment of a person's exposure to environmental pollutants. The ease of breath sampling that does not require patient transfer to hospitals and other health facilities is also attractive. Such tests are in demand in medicine, especially for diseases where early diagnosis is directly related to the effectiveness of treatment. However, despite its attractiveness and advantages, the strong biochemical rationale underlying this diagnostic approach and exuberance of research activity in the field for about twenty years, breath tests are still not approved and applied in routine clinical practice. The main goal of this Special Issue is to present studies that reveal and address the existing challenges and propose new solutions for different aspects of breath test development and applications, e.g. breath sampling, instrumental analysis, analysis strategies, data treatment.  

Prof. Dr. Andreas Tsakalof
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • breath analysis in disease diagnosis
  • breath analysis methodologies and methodologic challenges
  • biochemical and physiological background
  • breathomics, clinical applications and future perspectives
  • data treatment software and platforms
  • and VOCs as biomarkers of disease and exposure

Published Papers (2 papers)

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Research

17 pages, 1005 KiB  
Article
Modelling of Breath and Various Blood Volatilomic Profiles—Implications for Breath Volatile Analysis
by Paweł Mochalski, Julian King, Chris A. Mayhew and Karl Unterkofler
Molecules 2022, 27(8), 2381; https://doi.org/10.3390/molecules27082381 - 07 Apr 2022
Cited by 2 | Viewed by 2317
Abstract
Researchers looking for biomarkers from different sources, such as breath, urine, or blood, frequently search for specific patterns of volatile organic compounds (VOCs), often using pattern recognition or machine learning techniques. However, they are not generally aware that these patterns change depending on [...] Read more.
Researchers looking for biomarkers from different sources, such as breath, urine, or blood, frequently search for specific patterns of volatile organic compounds (VOCs), often using pattern recognition or machine learning techniques. However, they are not generally aware that these patterns change depending on the source they use. Therefore, we have created a simple model to demonstrate that the distribution patterns of VOCs in fat, mixed venous blood, alveolar air, and end-tidal breath are different. Our approach follows well-established models for the description of dynamic real-time breath concentration profiles. We start with a uniform distribution of end-tidal concentrations of selected VOCs and calculate the corresponding target concentrations. For this, we only need partition coefficients, mass balance, and the assumption of an equilibrium state, which avoids the need to know the volatiles’ metabolic rates and production rates within the different compartments. Full article
(This article belongs to the Special Issue State of the Art in Breath Analysis for Disease Diagnosis and Exposure Assessment: Challenges and Solutions)
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17 pages, 2873 KiB  
Article
pyAIR—A New Software Tool for Breathomics Applications—Searching for Markers in TD-GC-HRMS Analysis
by Lilach Yishai Aviram, Dana Marder, Hagit Prihed, Konstantin Tartakovsky, Daniel Shem-Tov, Regina Sinelnikov, Shai Dagan and Nitzan Tzanani
Molecules 2022, 27(7), 2063; https://doi.org/10.3390/molecules27072063 - 23 Mar 2022
Cited by 1 | Viewed by 2167
Abstract
Volatile metabolites in exhaled air have promising potential as diagnostic biomarkers. However, the combination of low mass, similar chemical composition, and low concentrations introduces the challenge of sorting the data to identify markers of value. In this paper, we report the development of [...] Read more.
Volatile metabolites in exhaled air have promising potential as diagnostic biomarkers. However, the combination of low mass, similar chemical composition, and low concentrations introduces the challenge of sorting the data to identify markers of value. In this paper, we report the development of pyAIR, a software tool for searching for volatile organic compounds (VOCs) markers in multi-group datasets, tailored for Thermal-Desorption Gas-Chromatography High Resolution Mass-Spectrometry (TD-GC-HRMS) output. pyAIR aligns the compounds between samples by spectral similarity coupled with retention times (RT), and statistically compares the groups for compounds that differ by intensity. This workflow was successfully tested and evaluated on gaseous samples spiked with 27 model VOCs at six concentrations, divided into three groups, down to 0.3 nL/L. All analytes were correctly detected and aligned. More than 80% were found to be significant markers with a p-value < 0.05; several were classified as possibly significant markers (p-value < 0.1), while a few were removed due to background level. In all group comparisons, low rates of false markers were found. These results showed the potential of pyAIR in the field of trace-level breathomics, with the capability to differentially examine several groups, such as stages of illness. Full article
(This article belongs to the Special Issue State of the Art in Breath Analysis for Disease Diagnosis and Exposure Assessment: Challenges and Solutions)
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