Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose

Currently, antibiotics are often prescribed to children without reason due to the inability to quickly establish the presence of a bacterial etiology of the disease. One way to obtain additional diagnostic information quickly is to study the volatile metabolome of biosamples using arrays of sensors. The goal of this work was to assess the possibility of using an array of chemical sensors with various sensitive coatings to determine the presence of a bacterial infection in children by analyzing the equilibrium gas phase (EGP) of urine samples. The EGP of 90 urine samples from children with and without a bacterial infection (urinary tract infection, soft tissue infection) was studied on the "MAG-8" device with seven piezoelectric sensors in a hospital. General urine analysis with sediment microscopy was performed using a Uriscan Pro analyzer and using an Olympus CX31 microscope. After surgical removal of the source of inflammation, the microbiological studies of the biomaterial were performed to determine the presence and type of the pathogen. The most informative output data of an array of sensors have been established for diagnosing bacterial pathology. Regression models were built to predict the presence of a bacterial infection in children with an error of no more than 15%. An indicator of infection is proposed to predict the presence of a bacterial infection in children with a high sensitivity of 96%.

Needle Trap Device-GC-MS for Characterization of Lung Diseases Based on Breath VOC Profiles

Volatile organic compounds (VOCs) have been assessed in breath samples as possible indicators of diseases. The present study aimed to quantify 29 VOCs (previously reported as potential biomarkers of lung diseases) in breath samples collected from controls and individuals with lung cancer, chronic obstructive pulmonary disease and asthma. Besides that, global VOC profiles were investigated. A needle trap device (NTD) was used as pre-concentration technique, associated to gas chromatography-mass spectrometry (GC-MS) analysis. Univariate and multivariate approaches were applied to assess VOC distributions according to the studied diseases. Limits of quantitation ranged from 0.003 to 6.21 ppbv and calculated relative standard deviations did not exceed 10%. At least 15 of the quantified targets presented themselves as discriminating features. A random forest (RF) method was performed in order to classify enrolled conditions according to VOCs' latent patterns, considering VOCs responses in global profiles. The developed model was based on 12 discriminating features and provided overall balanced accuracy of 85.7%. Ultimately, multinomial logistic regression (MLR) analysis was conducted using the concentration of the nine most discriminative targets (2-propanol, 3-methylpentane, (E)-ocimene, limonene, m-cymene, benzonitrile, undecane, terpineol, phenol) as input and provided an average overall accuracy of 95.5% for multiclass prediction.

Volatile Organic Compounds in Exhaled Breath as Fingerprints of Lung Cancer, Asthma and COPD

Lung cancer, chronic obstructive pulmonary disease (COPD) and asthma are inflammatory diseases that have risen worldwide, posing a major public health issue, encompassing not only physical and psychological morbidity and mortality, but also incurring significant societal costs. The leading cause of death worldwide by cancer is that of the lung, which, in large part, is a result of the disease often not being detected until a late stage. Although COPD and asthma are conditions with considerably lower mortality, they are extremely distressful to people and involve high healthcare overheads. Moreover, for these diseases, diagnostic methods are not only costly but are also invasive, thereby adding to people’s stress. It has been appreciated for many decades that the analysis of trace volatile organic compounds (VOCs) in exhaled breath could potentially provide cheaper, rapid, and non-invasive screening procedures to diagnose and monitor the above diseases of the lung. However, after decades of research associated with breath biomarker discovery, no breath VOC tests are clinically available. Reasons for this include the little consensus as to which breath volatiles (or pattern of volatiles) can be used to discriminate people with lung diseases, and our limited understanding of the biological origin of the identified VOCs. Lung disease diagnosis using breath VOCs is challenging. Nevertheless, the numerous studies of breath volatiles and lung disease provide guidance as to what volatiles need further investigation for use in differential diagnosis, highlight the urgent need for non-invasive clinical breath tests, illustrate the way forward for future studies, and provide significant guidance to achieve the goal of developing non-invasive diagnostic tests for lung disease. This review provides an overview of these issues from evaluating key studies that have been undertaken in the years 2010–2019, in order to present objective and comprehensive updated information that presents the progress that has been made in this field. The potential of this approach is highlighted, while strengths, weaknesses, opportunities, and threats are discussed. This review will be of interest to chemists, biologists, medical doctors and researchers involved in the development of analytical instruments for breath diagnosis.

An Optimistic Vision of Future: Diagnosis of Bacterial Infections by Sensing Their Associated Volatile Organic Compounds

Simple tests using sniff analysis that have the ability of diagnosing and rapidly distinguishing between infections due to different bacteria are urgently required by medical community worldwide. Professionals interested in this topic wish for these tests to be simultaneously cheap, fast, easily applicable, non-invasive, robust, reliable, and sensitive. Current analytical instrumentation has already the ability for performing real time (minutes or a few dozens of minutes) analysis of volatile bacterial biomarkers (the VOCs emitted by bacteria). Although many articles are available, a review displaying an objective evaluation of the current status in the field is still needed. This review tries to present an overview regarding the bacterial biomarkers released from in vitro cultivation of various bacterial strains and also from different biological matrices investigated, over the last 10 years. We have described results of relevant studies, which used modern analytical techniques to evaluate specific biomarker profiles associated with bacterial infections. Our purpose was to present a comprehensive view of available possibilities for detection of emitted bacterial VOCs from different matrices. We intend that this review to be of general interest for both medical doctors and for all researchers preoccupied with bacterial infectious diseases and their rapid diagnosis using analytical instrumentation.

Temporal influence of different antibiotics onto the inhibition of Escherichia coli bacterium grown in different media

Escherichia coli (E. coli) is a Gram-negative bacterium commonly found in the lower intestine of warm-blooded organisms, including humans. Although the majority of the strains are considerably harmless, some serotypes are pathogenic, frequently causing diarrhea and other illnesses outside the intestinal tract. The standard antidote against bacteria is the use of antibiotics. Depending on their type, the antibiotics have various mechanisms of action on bacteria. Moreover, in case of in-vitro cultivation of bacteria, the used growth media plays a crucial role, since it influences bacterial inhibition as well. In the present study, we emphasize the importance of cultivability in bacterial inhibition under the treatment with five different antibiotics belonging to different classes. Consequently, E. coli was cultivated in three different growth media: trypcase soy broth (TSB), Mueller Hinton (MH), and minimal salts (M9) enriched with glucose, respectively. MALDI-TOF MS (matrix-assisted laser desorption ionization time-of-flight mass spectrometry) analyses, that were used for fast characterization of changes that occur in ribosomal protein profiles, revealed differentiation and similarities between investigated cases, while flow cytometry (FCM) tests better explained the given changes that occurred in the analyzed samples after 3, 24 and 48 h of experimental campaign.