Exploring the performance of a functionalized CNT-based sensor array for breathomics through clustering and classification algorithms: from gas sensing of selective biomarkers to discrimination of chronic obstructive pulmonary disease

Drera, Giovanni; Freddi, Sonia; Emelianov, Aleksei V.; Bobrinetskiy, Ivan; Chiesa, Maria; Zanotti, Michele; Pagliara, Stefania; Fedorov, Fedor S.; Nasibulin, Albert G.; Montuschi, Paolo; Sangaletti, L.

doi:10.1039/d1ra03337a

Cited by 20 publications

(17 citation statements)

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“…Finally, two recent works investigate chronic obstructive pulmonary disease (COPD) with an electronic nosed composed of eight sensors based on SWCNTs functionalized with organic molecules [ 52 , 53 ].…”

Section: Resultsmentioning

confidence: 99%

“…To date, only an article reports on covalent functionalization of CNTs-based sensors to develop an electronic nose [ 43 ], whereas the majority deal with CNTs modified via non-covalent techniques, including drop-casting of molecules or nanoparticles in solution [ 34 , 38 , 41 , 45 , 50 ], thermal evaporation [ 37 , 52 , 53 ], spray layer-by-layer deposition [ 35 , 36 , 39 , 40 , 42 ], plasma post-discharge [ 46 ], or spin coating [ 51 ].…”

Section: Methodsmentioning

confidence: 99%

“…Online measurements have been conducted only in ref [ 49 , 52 , 53 ], and total breath has been analysed only in [ 52 ], [ 53 ], and [ 57 ]. Of note, the PTFE bag used by Freddi et al [ 52 ] and Drera et al [ 53 ] was aimed at both collecting the exhaled breath and hosting the e-nose during the measurements..…”

Section: Methodsmentioning

confidence: 99%

“…For almost every work it is clear that there is a balance in gender, average age and smoking habits in the studied population. When there is no balance, authors often prove that these factors do not influence the discrimination capability of the electronic nose [ 52 , 53 ].…”

Section: Methodsmentioning

confidence: 99%

“…Among the 26 articles found in literature reporting on CNTs-based electronic noses for breathomic applications, 20 of them present electronic noses completely based on CNTs-sensors [ 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 ], while 6 papers report on electronic noses that host both CNTs-sensors and NPs-based sensors [ 54 , 55 , 56 , 57 , 58 , 59 ]. All the electronic noses included in the latter group have been tested on the exhaled breath of patients, while only four electronic noses of the former group have been exposed to human breath [ 50 , 51 , 52 , 53 ], whereas 13 arrays have been tested only to target gases [ 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ]. Tests on simulated exhaled breath have been performed by two electronic noses [ 47 , 48 ] and one array has been exposed to the breath of rats [ ...…”

Section: Introductionmentioning

confidence: 99%

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Trends in the Development of Electronic Noses Based on Carbon Nanotubes Chemiresistors for Breathomics

Freddi¹,

Sangaletti²

2022

Nanomaterials

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The remarkable potential of breath analysis in medical care and diagnosis, and the consequent development of electronic noses, is currently attracting the interest of the research community. This is mainly due to the possibility of applying the technique for early diagnosis, screening campaigns, or tracking the effectiveness of treatment. Carbon nanotubes (CNTs) are known to be good candidates for gas sensing, and they have been recently considered for the development of electronic noses. The present work has the aim of reviewing the available literature on the development of CNTs-based electronic noses for breath analysis applications, detailing the functionalization procedure used to prepare the sensors, the breath sampling techniques, the statistical analysis methods, the diseases under investigation, and the population studied. The review is divided in two main sections: one focusing on the e-noses completely based on CNTs and one reporting on the e-noses that feature sensors based on CNTs, along with sensors based on other materials. Finally, a classification is presented among studies that report on the e-nose capability to discriminate biomarkers, simulated breath, and animal or human breath.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Trends in the Development of Electronic Noses Based on Carbon Nanotubes Chemiresistors for Breathomics

Freddi¹,

Sangaletti²

2022

Nanomaterials

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An Efficient Ambient‐Moisture–Driven Wearable Electrical Power Generator

Maity

Fussenegger

2023

Advanced Science

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Existing devices for generating electrical power from water vapor in ambient air require high levels of relative humidity (RH), cannot operate for prolonged periods, and provide insufficient output for most practical applications. Here a heterogeneous moisture-driven electrical power generator (MODEG) is developed in the form of a free-standing bilayer of polyelectrolyte films, one consisting of a hygroscopic matrix of graphene oxide(GO)/polyaniline(PANI) [(GO)PANI] and the other consisting of poly(diallyldimethylammonium chloride)(PDDA)-modified fluorinated Nafion (F-Nafion (PDDA)). One MODEG unit (1 cm 2 ) can deliver a stable open-circuit output of 0.9 V at 8 μA for more than 10 h with a matching external load. The device works over a wide range of temperature (−20 to +50 °C) and relative humidity (30% to 95% RH). It is shown that series and parallel combinations of MODEG units can directly supply sufficient power to drive commercial electronic devices such as light bulbs, supercapacitors, circuit boards, and screen displays. The (GO)PANI:F-Nafion (PDDA) hybrid film is embedded in a mask to harvest the energy from exhaled water vapor in human breath under real-life conditions. The device could consistently generate 450-600 mV during usual breathing, and provides sufficient power to drive medical devices, wearables, and emergency communication.

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Integrating routine blood biomarkers and artificial intelligence for supporting diagnosis of silicosis in engineered stone workers

Sanchez‐Morillo,

León‐Jiménez,

Guerrero‐Chanivet

et al. 2024

Bioengineering & Transla Med

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Engineered stone silicosis (ESS), primarily caused by inhaling respirable crystalline silica, poses a significant occupational health risk globally. ESS has no effective treatment and presents a rapid progression from simple silicosis (SS) to progressive massive fibrosis (PMF), with respiratory failure and death. Despite the use of diagnostic methods like chest x‐rays and high‐resolution computed tomography, early detection of silicosis remains challenging. Since routine blood tests have shown promise in detecting inflammatory markers associated with the disease, this study aims to assess whether routine blood biomarkers, coupled with machine learning techniques, can effectively differentiate between healthy individuals, subjects with SS, and PMF. To this end, 107 men diagnosed with silicosis, ex‐workers in the engineered stone (ES) sector, and 22 healthy male volunteers as controls not exposed to ES dust were recruited. Twenty‐one primary biochemical markers derived from peripheral blood extraction were obtained retrospectively from clinical hospital records. Relief‐F features selection technique was applied, and the resulting subset of 11 biomarkers was used to build five machine learning models, demonstrating high performance with sensitivities and specificities in the best case greater than 82% and 89%, respectively. The percentage of lymphocytes, the angiotensin‐converting enzyme, and lactate dehydrogenase indexes were revealed, among others, as blood biomarkers with significant cumulative importance for the machine learning models. Our study reveals that these biomarkers could detect a chronic inflammatory status and potentially serve as a supportive tool for the diagnosis, monitoring, and early detection of the progression of silicosis.

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Exploring the performance of a functionalized CNT-based sensor array for breathomics through clustering and classification algorithms: from gas sensing of selective biomarkers to discrimination of chronic obstructive pulmonary disease

Abstract: Extensive application of clustering and classification algorithms shows the potential of a CNT-based sensor array in breathomics.

Cited by 20 publications

References 101 publications

Trends in the Development of Electronic Noses Based on Carbon Nanotubes Chemiresistors for Breathomics

Trends in the Development of Electronic Noses Based on Carbon Nanotubes Chemiresistors for Breathomics

An Efficient Ambient‐Moisture–Driven Wearable Electrical Power Generator

Integrating routine blood biomarkers and artificial intelligence for supporting diagnosis of silicosis in engineered stone workers

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