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Synergy between nanomaterials and volatile organic compounds for non-invasive medical evaluation
Abstract
This article is an overview of the present and ongoing developments in the field of nanomaterial-based sensors for enabling fast, relatively inexpensive and minimally (or non-) invasive diagnostics of health conditions with follow-up by detecting volatile organic compounds (VOCs) excreted from one or combination of human body fluids and tissues (e.g., blood, urine, breath, skin). Part of the review provides a didactic examination of the concepts and approaches related to emerging sensing materials and transduction techniques linked with the VOC-based non-invasive medical evaluations. We also present and discuss diverse characteristics of these innovative sensors, such as their mode of operation, sensitivity, selectivity and response time, as well as the major approaches proposed for enhancing their ability as hybrid sensors to afford multidimensional sensing and information-based sensing. The other parts of the review give an updated compilation of the past and currently available VOC-based sensors for disease diagnostics. This compilation summarizes all VOCs identified in relation to sickness and sampling origin that links these data with advanced nanomaterial-based sensing technologies. Both strength and pitfalls are discussed and criticized, particularly from the perspective of the information and communication era. Further ideas regarding improvement of sensors, sensor arrays, sensing devices and the proposed workflow are also included.
... This approach may be crucial for early disease diagnosis based on nanomaterials to attain low-cost/low-end and easy-to-use detectors of breath volatiles as disease markers. attention among scientists [4]. Due to their volatility and small molecular size, VOCs generated through the metabolism of cells are mostly secreted through the exhaled breath (34%), reflecting a quantitative-qualitative correlation with various kinds of diseases. ...
... It has been well-documented that VOCs generated from cell metabolic activities can provide useful information on the health status of an organism and, therefore, be used as novel biomarkers for diagnostic purposes [2,3]. The detection of different types of diseases, including gastric or breast cancer, intestinal diseases, neurological diseases (Parkinson's and Alzheimer diseases, multiple sclerosis), diabetes mellitus, and tuberculosis using VOCs has attracted increasing breast cancer, intestinal diseases, neurological diseases (Parkinson's and Alzheimer diseases, multiple sclerosis), diabetes mellitus, and tuberculosis using VOCs has attracted increasing attention among scientists [4]. Due to their volatility and small molecular size, VOCs generated through the metabolism of cells are mostly secreted through the exhaled breath (34%), reflecting a quantitative-qualitative correlation with various kinds of diseases. ...
... Advances in VOC detection have been aided by the development of nanomaterialbased devices characterized by a high surface-to-volume ratio, fast response and recovery times, miniaturization and low power consumption, etc. [4,21,22]. ...
This work focuses on the possible application of gold nanoparticles on flexible cotton fabric as acetone- and ethanol-sensitive substrates by means of impedance measurements. Specifically, citrate- and polyvinylpyrrolidone (PVP)-functionalized gold nanoparticles (Au NPs) were synthesized using green and well-established procedures and deposited on cotton fabric. A complete structural and morphological characterization was conducted using UV–VIS and Fourier transform infrared (FT–IR) spectroscopy, atomic force microscopy (AFM), and scanning electron microscopy (SEM). A detailed dielectric characterization of the blank substrate revealed interfacial polarization effects related to both Au NPs and their specific surface functionalization. For instance, by entirely coating the cotton fabric (i.e., by creating a more insulating matrix), PVP was found to increase the sample resistance, i.e., to decrease the electrical interconnection of Au NPs with respect to citrate functionalized sample. However, it was observed that citrate functionalization provided a uniform distribution of Au NPs, which reduced their spacing and, therefore, facilitated electron transport. Regarding the detection of volatile organic compounds (VOCs), electrochemical impedance spectroscopy (EIS) measurements showed that hydrogen bonding and the resulting proton migration impedance are instrumental in distinguishing ethanol and acetone. Such findings can pave the way for the development of VOC sensors integrated into personal protective equipment and wearable telemedicine devices. This approach may be crucial for early disease diagnosis based on nanomaterials to attain low-cost/low-end and easy-to-use detectors of breath volatiles as disease markers.
... Carbon-based nanomaterials (e.g., graphene, carbon nanotubes (CNTs)) have been studied for the development of gas-sensor-wearables [41,42], due to their physicochemical properties, RT-sensing ability, and also their compatibility with other nanomaterials for enhanced performance [41,42]. In particular, graphene and its derivatives, such as graphene oxide have been found to be great at detecting execution and are promising gassensitive materials. ...
... Carbon-based nanomaterials (e.g., graphene, carbon nanotubes (CNTs)) have been studied for the development of gas-sensor-wearables [41,42], due to their physicochemical properties, RT-sensing ability, and also their compatibility with other nanomaterials for enhanced performance [41,42]. In particular, graphene and its derivatives, such as graphene oxide have been found to be great at detecting execution and are promising gassensitive materials. ...
... Carbon-based nanomaterials (e.g., graphene, carbon nanotubes (CNTs)) have been studied for the development of gas-sensor-wearables [41,42], due to their physicochemical properties, RT-sensing ability, and also their compatibility with other nanomaterials for enhanced performance [41,42]. In particular, graphene and its derivatives, such as graphene oxide have been found to be great at detecting execution and are promising gas-sensitive materials. ...
Early-stage, precise disease diagnosis and treatment has been a crucial topic of scientific discussion since time immemorial. When these factors are combined with experience and scientific knowledge, they can benefit not only the patient, but also, by extension, the entire health system. The development of rapidly growing novel technologies allows for accurate diagnosis and treatment of disease. Nanomedicine can contribute to exhaled breath analysis (EBA) for disease diagnosis, providing nanomaterials and improving sensing performance and detection sensitivity. Through EBA, gas-based nano-sensors might be applied for the detection of various essential diseases, since some of their metabolic products are detectable and measurable in the exhaled breath. The design and development of innovative nanomaterial-based sensor devices for the detection of specific biomarkers in breath samples has emerged as a promising research field for the non-invasive accurate diagnosis of several diseases. EBA would be an inexpensive and widely available commercial tool that could also be used as a disease self-test kit. Thus, it could guide patients to the proper specialty, bypassing those expensive tests, resulting, hence, in earlier diagnosis, treatment, and thus a better quality of life. In this review, some of the most prevalent types of sensors used in breath-sample analysis are presented in parallel with the common diseases that might be diagnosed through EBA, highlighting the impact of incorporating new technological achievements in the clinical routine.
... Moreover, VOCs at low concentrations can easily cause serious respiratory problems. For example, formaldehyde at very low concentrations (0.75 ppm) can cause cancer [2]. Therefore, convenient gas sensors with a low detection limit, high response, and low energy consumption are needed urgently. ...
... (2) Figure S8 shows the FTIR spectra of 10% Ni-ZnO sea urchins and the corresponding precursor. The main characteristic peaks at 472, 837, 1416, and 1510 cm −1 ( Figure S8a) were attributed to the CO 2 3− bending vibrations in the precursor. The peak at ca. 3391 cm −1 can be assigned to the -OH group in the precursor. ...
... Because some peaks referring to Ni-O in NiO overlapped with those of Zn-O in ZnO, there is only a characteristic peak ranging from 430 cm −1 to 440 cm −1 in the FTIR spectrum. The characteristic peaks associated with the CO 2 3− bending vibrations have disappeared due to the thorough decomposition of carbonate in the precursor to CO 2 and H 2 O. In addition, two weak peaks at 1386 and 1638 cm −1 were associated with the O-H bending vibration of the H 2 O molecule absorbed on Ni-doped ZnO sea urchins [35,36]. ...
Porous sea urchin-like nickel-doped ZnO with various nickel contents and high specific surface area were synthesized using a solution method followed by calcination. The nickel-doped ZnO products consisted of numerous porous nanoleaves. The Ni content in these products ranged from 5% to 20%. The Ni dopants in the ZnO lattice were verified by X-ray diffraction and X-ray photoelectron spectroscopy. The sensors based on nickel-doped ZnO sea urchins showed superior sensing performance for some volatile organic compounds (VOCs). ZnO sea urchins with 10% nickel doping exhibited the best gas-sensing performance, including a low working temperature, short response/recovery time, and high sensor response. In particular, the 10% Ni-doped ZnO sea urchin sensor exhibited a response of 84.4 with response/recovery times of 17/20 s towards 100 ppm formaldehyde vapor. These superior sensing behaviors were attributed mainly to a suitable Ni content with high content of oxygen defects, small nanocrystals, and a porous hierarchical structure with a high specific surface area.
... The medical and scientific communities are working together to develop fast, low cost, low-power, portable, and non-invasive diagnostic instruments, which can be accepted by the population, easy to access and widespread in health systems, overcoming all the barriers that cause a delay in cancer diagnosis. Electronic noses (e-noses), devices based on gas sensor arrays, constitute a recognized technology that is mature enough to enter clinical practice by satisfying all the above-mentioned requirements [2]- [5]. An e-nose, whose general architecture is depicted in Fig. 1, is an electronic sensing device intended to detect odors or flavors as global fingerprint with no separative mechanism. ...
... In the figure, the sensor array of the enose is exposed to a complex odor j. The electric signals from the sensors are conditioned by the analog front-end (AFE) circuit and then converted from the analog domain to ADC X (t) 2,j X (t) 3,j X (t) the digital domain by means of an analog-to-digital converter (ADC). The digitized signals are pre-processed to extract the sensor features, i.e., x n,j in Fig. 1. ...
Since hundreds of volatile organic compounds (VOCs) produced by cell metabolism and released into the blood are excreted through exhaled breath or body fluids, the volatile composition (volatilome) of human samples reflects a subject’s state of health and early signals any abnormal deviation from healthy to disease. The chemical volatilomic profile of biological matrices can be transduced in a digital fingerprint by low cost and easy-to-use electronic nose (e-nose) devices based on gas sensor arrays. The e-noses can be used to aid clinical diagnosis supporting conventional diagnostic methods that sometimes require expensive or invasive medical procedures and delays in diagnoses. In this paper, an e-nose devoted to the human volatilome fingerprinting is presented. The device, code-named SPYROX, adopts an array of 8 metal-oxide (MOX) gas sensors and it is able to analyze response signals from different matrices (multi-matrix samples), dealing with exhaled breath and headspace analysis of human biological samples. While other works in literature neglect the design of the interface circuit, here an optimal multi-ranged analog front-end (AFE) circuit is proposed. It aims to the optimization of the read-out sensitivity which, ultimately, leads to accurate training datasets and, consequently, to high classification scores. Finally, the efficacy of the device is proved by testing both chemical standards and mixtures. As a result, a classification accuracy of 100% is achieved with a linear discriminant model. The experimental results give a proof on the system’s efficacy to the fingerprint analysis of complex gas mixtures, which are typical of human volatilome.
... Another promising way to obtain best possible results is the use of hybrid sensor arrays, including different technologies as presented by (Broza et al., 2018). Interestingly, these hybrid arrays explicitly include the measurement of interfering VOCs to allow for clearer observation. ...
... It can, however, be crucial to choose a proper subset of the hybrid array so that the test-set error can be further reduced. For example, the entire hybrid array may not perform better than an array with only one technology, but a subset of the sensors from the hybrid array does (Broza et al., 2018). Such approaches are to date only scarcely used for VOC detection. ...
Wound infections are a major problem worldwide, both for the healthcare system and for patients affected. Currently available diagnostic methods to determine the responsible germs are time-consuming and costly. Wound infections are mostly caused by various bacteria, which in turn produce volatile organic compounds. From clinical experience, we know that depending on the bacteria involved, a specific odor impression can be expected. For this reason, we hypothesized that electronic noses, i.e., non-invasive electronic sensors for the detection of volatile organic compounds, are applicable for diagnostic purposes. By providing a comprehensive overview of the state-of-research, we tested our hypothesis. In particular, we addressed three overarching questions: 1) which sensor technologies are suitable for the diagnosis of wound infections and why? 2) how must the (biological) sample be prepared and presented to the measurement system? 3) which machine learning methods and algorithms have already proven successful for the classification of microorganisms? The corresponding articles have critically been reviewed and are discussed particularly in the context of their potential for clinical diagnostics. In summary, it can already be stated today that the use of electronic noses for the detection of bacteria in wound infections is a very interesting, fast and non-invasive method. However, reliable clinical studies are still missing and further research is necessary.
... Organic short-chain fatty acids such as propionic, succinic, and butyric acids, etc., are among the main end products of processes that occur in glands and the microbial fermentation of carbohydrates in the stomach [11,12]. They are also involved in the modulation of cytokines during inflammatory processes [13][14][15]. In addition, a correlation has been evidenced between endogenous VOCs expressed in saliva and those in blood. ...
... and the microbial fermentation of carbohydrates in the stomach [11,12]. They are also involved in the modulation of cytokines during inflammatory processes [13][14][15]. In addition, a correlation has been evidenced between endogenous VOCs expressed in saliva and those in blood. ...
Volatile organic compounds (VOCs) have recently received considerable attention for the analysis and monitoring of different biochemical processes in biological systems such as humans, plants, and microorganisms. The advantage of using VOCs to gather information about a specific process is that they can be extracted using different types of samples, even at low concentrations. Therefore, VOC levels represent the fingerprints of specific biochemical processes. The aim of this work was to develop a sensor based on a photoionization detector (PID) and a zeolite layer, used as an alternative analytic separation technique for the analysis of VOCs. The identification of VOCs occurred through the evaluation of the emissive profile during the thermal desorption phase, using a stainless-steel chamber for analysis. Emission profiles were evaluated using a double exponential mathematical model, which fit well if compared with the physical system, describing both the evaporation and diffusion processes. The results showed that the zeolite layer was selective for propionic acid molecules if compared to succinic acid molecules, showing linear behavior even at low concentrations. The process to define the optimal adsorption time between the propionic acid molecules was performed in the range of 5 to 60 min, followed by a thermal desorption process at 100 °C. An investigation of the relationship between the evaporation and diffusion rates showed that the maximum concentration of detected propionic acid molecules occurred in 15 min. Other analyses were performed to study how the concentration of VOCs depended on the desorption temperature and the volume of the analysis chamber. For this purpose, tests were performed using three analysis chambers with volumes of 25 × 10−6, 50 × 10−6, and 150 × 10−6 m3 at three different desorption temperatures of 20 °C, 50 °C, and 100 °C, respectively. The results demonstrated that the evaporation rate of the VOCs increased rapidly with an increasing temperature, while the diffusion rate remained almost constant and was characterized by a slow decay time. The diffusion ratio increased when using a chamber with a larger volume. These results highlight the capabilities of this alternative technique for VOC analysis, even for samples with low concentrations. The coupling of a zeolite layer and a PID improves the detection selectivity in portable devices, demonstrating the feasibility of extending its use to a wide range of new applications.
... As stated in the Introduction, mainly selected-ion flowtube mass spectrometry or PTR-MS methods are used for breath testing. 1,36 These methods, in addition to being expensive and requiring trained personnel, have a low LOD and excellent detection selectivity. However, the development of noninvasive methods is inevitable and vital. ...
... 4 For example, ammonia in the breath can be associated with asthma, chronic renal failure/uremia, gastrointestinal disease, halitosis, and pulmonary arterial hypertension. 1 The pH indicators react with both acidic and basic compounds, and their color changes. It should be noted that the colors used include BP and BG, which have pH ranges of the color change of 3.8−5.4 ...
Alginate/Ni-Al-layered double hydroxide/dye (Alg/Ni-Al-LDH/dye) composite films were fabricated using the solution casting method. The dyes used included methyl red, phenol red, thymol blue, bromothymol blue, m-cresol purple, methyl orange, bromocresol purple (BP), and bromocresol green (BG) in the overall pH range of 3.8 to 9.6. The chemical composition and morphology of the Alg/Ni-Al-LDH/dye composite film structure were investigated by Fourier transform infrared spectroscopy, FESEM, atomic force microscopy, and X-ray diffraction. The Alg/Ni-Al-LDH/dye composite films were semitransparent and mechanically flexible. Acetic acid was investigated as a respiratory biomarker related to gastrointestinal diseases. The parameters studied included color volume, response time, Ni-Al-LDH nanosheet volume, reusability, and drawing of the calibration curve along with statistical features including standard deviation, relative standard deviation, limit of detection, and limit of quantitation. Colorimetric indicators BP and BG in the presence of acetic acid produce color changes that are almost visible to the naked eye. However, other used indicators have shown almost no change. Therefore, it can be reported that the sensors made in the presence of BP and BG act selectively in relation to acetic acid.
... Therefore, the detection of the VOCs plays an important role for human health and is the primary step to decipher the complex interaction mechanisms between VOCs and human olfaction [4]. The identification and discrimination of these VOC molecules can be realized by utilizing changes in the electronic response of the sensor materials upon adsorption [5][6][7]. ...
Understanding the interaction mechanisms between volatile organic compounds (VOCs) with graphene-based materials is the primary and crucial step for human health and the advancement of digital olfaction. In this study, we investigated the adsorption behavior of four common odor molecules (toluene, ethanol, 2-Furfurylthiol, and guaiacol) on various graphene-based substrates, including pristine graphene, graphene doped with single graphitic-N atom (GR-N), and multiple pyrodinic-N atoms (1pd-N, 2pd-N, 3pd-N, and 4pd-N) using density functional theory. The adsorption energies and Bader charge analysis for all adsorption cases demonstrated that the molecules were weak physisorbed on all substrates. Through the work function change comparison, 2pd-N and N-gra presents likely promising sensing performance towards the odor molecules, while the selectivity declines by further introducing 3 and 4 pyrodinic-N atoms into graphene. The surface dipole moment analysis shed light on the underlying mechanism of work function change and explained the reduced sensitivity and selectivity observed for 3pd-N and 4pd-N, which can be attributed to a decrease in the molecule-induced dipole moment and increase in spatial charge redistribution. These findings could contribute to the fundamental understanding of odor molecule-graphene interactions and provide insights for the design and optimization of graphene-based electronic olfaction devices.
... [6][7][8] . These VOCs could act as biomarkers for the diagnostic of particular diseases [9][10][11][12][13][14][15][16] . Ethyl butyrate (C 6 H 12 O 2 ) [17][18][19][20] and heptanal (C 7 H 14 O) 4,21,22 are the key biomarkers released from exhaled breath of the COVID-19 patients. ...
Motivated by the necessity of efficient detection of COVID-19 through specific biomarkers, such as ethyl butyrate and heptanal, we performed first principles calculations based on density functional theory (DFT) to explore the sensing mechanism of pure, vacancy-induced, and single atom catalyzed CrX2 (X = Se, Te) monolayers. Both the biomarkers barely bind on pristine CrSe2. However with Se-vacancy (As-doping) suitable adsorption energies of −1.44 (−0.70), and −0.70 (−0.54) eV were obtained for ethyl butyrate and heptanal, respectively. Te-vacancy (Sn-doping) in CrTe2 resulted in much stronger binding of ethyl butyrate and heptanal with the adsorption energies of −2.04 (−2.40), and −2.90 (−2.40) eV, respectively. The adsorption of the mentioned biomarkers altered the magnetic and electronic properties of defected CrX2, which were explored through spin-polarized density of states, electrostatic potential and work function calculations. Measurable changes in electronic and magnetic properties confirmed excellent sensing potential of CrX2. Statistical thermodynamics analysis based on Langmuir adsorption model was employed to study the sensing of the biomarkers at different temperature and pressure ranges for real-world application.
... To attain heightened sensitivities at levels below parts per billion (ppb), metal ions or other substances, such as polymers, were typically utilised to decorate MOS and form hybrid composites [47]. In addition, numerous documented instances indicate that the sensitivity and efficacy of MOS can be adjusted through the regulation of various parameters, including but not limited to design, structure, morphology, surface area, and operating temperature [48,49]. Thus, significant improvements in the detection of VOCs have been observed in MOS structures with enormous surface area and little volume, according to the parameters examined. ...
The proliferation of point-of-use (PoU) or point-of-care (PoC) detecting technologies has resulted in a significant expansion of miniaturized sensors that were indispensable in the battle against pollution, arising contaminants, and pandemics. These sensors enable immediate identification of gases and airborne pathogens. Notwithstanding, the economical fabrication of miniature gas sensors, while maintaining their selectivity, sensitivity, and response time, presents a significant challenge. To address the aforementioned constraints, microfluidic technology has been utilized as a potential solution, rendering it a highly favorable option for PoU or PoC applications. Microfluidic-based gas sensors, while showing promising results, are still in their infancy. This review focuses on emerging trends in the synthesis of novel materials and their application is microfluidic gas sensors. Further, the challenges pertaining to this sensing and future perspective with the possible solution have been discussed.
... Humans release a diverse array of volatile organic compounds (VOCs) [1]. Since some of those human-borne VOCs (H-VOCs) include metabolites produced in human biological activities, studies of them have been actively conducted to realize disease screening and metabolic monitoring [2][3][4]. While the majority of the H-VOCs are devoid of odor, there are specific odorous chemicals within H-VOCs that contribute to body odor [5][6][7]. ...
The molecule 2-nonenal is renowned as the origin of unpleasant human aging-related body odor that can potentially indicate age-related metabolic changes. Most 2-nonenal measurements rely on chromatographic analytical systems, which pose challenges in terms of daily usage and the ability to track changes in concentration over time. In this study, we have developed liquid-and gas-phase biosensors (bio-sniffers) with the aim of enabling facile and continuous measurement of trans-2-nonenal vapor. Initially, we compared two types of nicotinamide adenine dinucleotide (phosphate) [NAD(P)]-dependent enzymes that have the catalytic ability of trans-2-nonenal: alde-hyde dehydrogenase (ALDH) and enone reductase 1 (ER1). The developed sensor quantified the trans-2-nonanal concentration by measuring fluorescence (excitation: 340 nm, emission: 490 nm) emitted from NAD(P)H that was generated or consumed by ALDH or ER1. The ALDH biosensor reacted to a variety of aldehydes including trans-2-nonenal, whereas the ER1 biosensor showed high selectivity. In contrast, the ALDH bio-sniffer showed quantitative characteristics for trans-2-nonenal vapor at a concentration range of 0.4-7.5 ppm (with a theoretical limit of detection (LOD) and limit of quantification (LOQ) of 0.23 and 0.26 ppm, respectively), including a reported concentration (0.85-4.35 ppm), whereas the ER1 bio-sniffer detected only 0.4 and 0.8 ppm. Based on these findings, headspace gas of skin-wiped alcohol-absorbed cotton collected from study participants in their 20s and 50s was measured by the ALDH bio-sniffer. Consequently, age-related differences in signals were observed, suggesting the potential for measuring trans-2-nonenal vapor.
... The modern development in flexible electronics, mechanics, material science, and manufacturing engineering allows the production of piezotronic devices in precise dimensions. Significant progress has been made in the study of piezoelectric materials [49][50][51][52][53][54][55], their numerous nanostructures [56][57][58][59][60][61], piezotronic devices and their ongoing trends [62][63][64][65][66][67][68][69][70][71], performance improvement strategies [72][73][74][75][76][77][78][79], hybridization tactics [80][81][82][83][84][85][86][87][88] to provide synergy [89][90][91][92][93][94], multi-directionality [95,96], flexible and wearable platforms [97][98][99][100], etc. With the advantages of enhanced piezoelectric effect, excellent mechanical properties, and emerging nanotechnology applications, one-dimensional (1D) ZnO nanostructures have been considered as the most promising inorganic piezoelectric nanomaterial [101][102][103][104][105]. Therefore, enormous attention is required in 1D ZnO nanostructures by considering (a) rational design and material engineering, (b) miniaturization of various functional devices, (c) their high specific surface area, (d) easier integration of multifunctionality, E-mail address: Ramesh.Ghosh@glasgow.ac.uk. ...
Piezotronic sensors and self-powered gadgets are highly sought-after for flexible, wearable, and intelligent electronics
for their applications in cutting-edge healthcare and human-machine interfaces. With the advantages of a
well-known piezoelectric effect, excellent mechanical properties, and emerging nanotechnology applications,
one-dimensional (1D) ZnO nanostructures organized in the form of a regular array have been regarded as one of
the most promising inorganic active materials for piezotronics. This report intends to review the recent developments
of 1D ZnO nanostructure arrays for multifunctional piezotronic sensors. Prior to discussing rational design
and fabrication approaches for piezotronic devices in precisely controlled dimensions, well-established synthesis
methods for high-quality and well-controlled 1D ZnO nanostructures are addressed. The challenges associated
with the well-aligned, site-specific synthesis of 1D ZnO nanostructures, development trends of piezotronic devices,
advantages of an ordered array of 1D ZnO in device performances, exploring new sensing mechanisms, incorporating
new functionalities by constructing heterostructures, the development of novel flexible device integration
technology, the deployment of novel synergistic strategies in piezotronic device performances, and potential
multifunctional applications are covered. A brief evaluation of the end products, such as small-scale
miniaturized unconventional power sources in sensors, high-resolution image sensors, and personalized healthcare
medical devices, is also included. The paper is summarized towards the conclusion by outlining the present
difficulties and promising future directions. This study will provide guidance for future research directions in 1D
ZnO nanostructure-based piezotronics, which will hasten the development of multifunctional devices, sensors,
chips for human-machine interfaces, displays, and self-powered systems.
... An abnormal pattern of VOC concentrations that deviates from the healthy pattern may indicate either TB infection or a high risk of infection with TB. The collected VOCs will then be fed into a set of specially-designed nanomaterial-based sensors capable of detecting a variety of skin-based TB VOCs [3][4][5][6]. Finally, the sensors will translate these collected VOCs into the time series of resistance signals. Ultimately, the output multivariate time series (MTS) sensor signals will be used as feature inputs in ML models for the final discrimination between positive TB cases and healthy controls. ...
Tuberculosis (TB) has long been recognized as a significant health concern worldwide. Recent advancements in noninvasive wearable devices and machine learning (ML) techniques have enabled rapid and cost-effective testing for the real-time detection of TB. However, small datasets are often encountered in biomedical and chemical engineering domains, which can hinder the success of ML models and result in overfitting issues. To address this challenge, we propose various data preprocessing methods and ML approaches, including long short-term memory (LSTM), convolutional neural network (CNN), Gramian angular field-CNN (GAF-CNN), and multivariate time series with MinCutPool (MT-MinCutPool), for classifying a small TB dataset consisting of multivariate time series (MTS) sensor signals. Our proposed methods are compared with state-of-the-art models commonly used in MTS classification (MTSC) tasks. We find that lightweight models are more appropriate for small-dataset problems. Our experimental results demonstrate that the average performance of our proposed models outperformed the baseline methods in all aspects. Specifically, the GAF-CNN model achieved the highest accuracy of 0.639 and the highest specificity of 0.777, indicating its superior effectiveness for MTSC tasks. Furthermore, our proposed MT-MinCutPool model surpassed the baseline MTPool model in all evaluation metrics, demonstrating its viability for MTSC tasks.
... In addition, the acetone concentration in respiratory gases of diabetic persons (over 1.8 ppm) is higher than those healthy individuals in the range of 0.3-0.9 ppm [2,3]. The effective acetone detection is used for diabetes diagnoses with the advantages of being non-invasive and painless. ...
Although individual γ-Fe2O3 and α-Fe2O3 have been widely fabricated for gas sensors, their mixed phase of α/γ-Fe2O3 might deliver excellent sensing properties. In this study, a facile solvothermal method was used to fabricate Fe-alkoxide. After thermal treatment, it was converted into γ-Fe2O3, α-Fe2O3 and their mixed-phase α/γ-Fe2O3 with a nanosheets-assembled flower-like structure. We studied the influence of calcination temperature on the phase and sensing properties on acetone detection. The α/γ-Fe2O3 which annealed at 400 °C included 18% α-Fe2O3 and it exhibited excellent sensing performance towards acetone compared to that of γ-Fe2O3 and α-Fe2O3. It showed a response of 353 to acetone with a concentration of 200 ppm, and a low limit of detection of 0.5 ppm at 160 °C. In addition, the change in responses with acetone concentration from 50 to 200 ppm shows a good linear relationship. Moreover, this material has good reproducibility and selectivity as well as a fast response time of 22 s and recovery time of 14 s to 200 ppm. Therefore, our mixed phase of α/γ-Fe2O3 possesses great prospects for acetone detection.
... Owing to this relationship, developing a cost−effective and reliable exhaled breath sensing device is urgent. Currently, a variety of acetone detection methods have been reported, including colorimetric sensors [15,16], optical sensors [17,18], metal oxide sensors [8,19], monolayer−coated metal nanoparticle sensors [20], etc. Liao et al. demonstrated the detection of acetone using a luminescent chemosensor. When europium (Eu)−containing covalent organic framework (DhaTab−COF−EuIL) was exposed to acetone, it revealed significant luminescence quenching toward acetone caused by competitive absorption of the light source's energy and led to the transfer of photoinduced energy [21]. ...
Human−exhaled breath mainly contains water, oxygen, carbon dioxide, and endogenous gases closely related to human metabolism. The linear relationship between breath acetone and blood glucose concentration has been revealed when monitoring diabetes patients. Considerable attention has been directed toward developing a highly sensitive volatile organic compounds (VOCs) sensing material that can detect breath acetone. In this study, we propose a tungsten oxide/tin oxide/silver/poly (methyl methacrylate) (WO3/SnO2/Ag/PMMA) sensing material fabricated using the electrospinning technique. By monitoring the evolution of sensing materials’ extinction spectra, low concentrations of acetone vapor can be detected. Moreover, the interfaces between SnO2 and WO3 nanocrystals construct n−n junctions, which generate more electron–hole pairs than those without such structure when the light strikes. This helps to improve the sensitivity of sensing materials when they are subjected to acetone surroundings. The established sensing materials (WO3/SnO2/Ag/PMMA) exhibit a sensing limit of 20 ppm for acetone vapor and show specificity for acetone even in ambient humidity.
... For the objective of monitoring COVID-19, screening of expelled breath may be a less intrusive form of analysis (Corman et al. 2020;Broza et al. 2018). However, screening SARS-CoV-2 from exhaled air has proven to be quite complicated. ...
The outbreak of COVID-19 has caused great havoc and affected many parts of the world. It has imposed a great challenge to the medical and health fraternity with its ability to continue mutating and increasing the transmission rate. Some challenges include the availability of current knowledge of active drugs against the virus, mode of delivery of the medicaments, its diagnosis, which are relatively limited and do not suffice for further prognosis. One recently developed drug delivery system called nanoparticles is currently being utilized in combating COVID-19. This article highlights the existing methods for diagnosis of COVID-19 such as computed tomography scan, reverse transcription-polymerase chain reaction, nucleic acid sequencing, immunoassay, point-of-care test, detection from breath, nanotechnology-based bio-sensors, viral antigen detection, microfluidic device, magnetic nanosensor, magnetic resonance platform and internet-of-things biosensors. The latest detection strategy based on nanotechnology, biosensor, is said to produce satisfactory results in recognizing SARS-CoV-2 virus. It also highlights the successes in the research and development of COVID-19 treatments and vaccines that are already in use. In addition, there are a number of nanovaccines and nanomedicines currently in clinical trials that have the potential to target COVID-19.
... However, it presents drawbacks such as high costs, time/energy consumption and the need for skilled professionals [6]. Conversely, sensor-based techniques, being highly sensitive, low cost and easy-to-use in compact systems [7], have a great potential in early diagnosis of diseases [8]. Here, we propose a nanomaterial-based chemoresistive sensor as a promising alternative to traditional diagnostic tools. ...
The COVID-19 pandemic outbreak, declared in March 2020, has led to several behavioral changes in the general population, such as social distancing and mask usage among others. Furthermore, the sanitary emergency has stressed health system weaknesses in terms of disease prevention, diagnosis, and cure. Thus, smart technologies allowing for early and quick detection of diseases are called for. In this framework, the development of point-of-care devices can provide new solutions for sanitary emergencies management. This work focuses on the development of useful tools for early disease diagnosis based on nanomaterials on cotton substrates, to obtain a low-cost and easy-to-use detector of breath volatiles as disease markers. Specifically, we report encouraging experimental results concerning acetone detection through impedance measurements. Such findings can pave the way to the implementation of VOCs (Volatile Organic Compounds) sensors into smart and user friendly diagnostic devices.
... Under specific circumstances, the resulting polyvinyl chloride or latex could, for instance, be solubilized or chemically changed. Several of these natural polymers could be made into nanowires, allowing them to be used in the creation of liquid and gas-phase ultra-filtration systems, as well as sensors (Broza et al. 2018). Certain readily biodegradable nanofibers could be employed in medicine to help with tissue regeneration and drug release management (Tomalia 2004;Priya et al. 2022). ...
... Hence, detection of VOCs can be a non-invasive and convenient method for early diagnosis of diseases and monitoring to control disease for complications at early stage. There are different techniques that have been developed to date to detect VOCs accurately such as Proton Transfer Reaction-Mass Spectrometry (PTR-MS), Selected Ion Flow Tube (SIFT-MS), laser spectroscopy, and Gas Chromatography (GC) [17,36,37]. Though these techniques are very accurate at detecting disease-related VOCs, they are very expensive and require high levels of experience to operate the instruments. ...
Human breath contains over 3000 volatile organic compounds, abnormal concentrations of which can indicate the presence of certain diseases. Recently, metal-organic framework (MOF)-metal oxide composite materials have been explored for chemiresistive sensor applications, however their ability to detect breath compounds associated with specific diseases remains unknown. In this work, we present a new high-throughput computational protocol for evaluating the sensing ability of MOF-metal oxide towards small organic compounds. This protocol uses a cluster-based method for accelerated structure relaxation, and a combination of binding energies and density-of-states analysis to evaluate sensing ability, the latter measured using Wasserstein distances. We apply this protocol to the case of the MOF-metal oxide composite material NM125-TiO2 and show that it is consistent with previously reported experimental results for this system. We examine the sensing ability of NM125-TiO2 for over 100 human-breath compounds spanning 13 different diseases. Statistical inference then allows us to identifies ones which subsequent experimental efforts should focus on. Overall, this work provides new tools for computational sensor research, while also illustrating how computational materials science can be integrated into the field of preventative medicine.
Volatile Organic Compounds (VOC) are a major class of environmental pollutants hazardous to human health, but also highly relevant in other fields including early disease diagnostics and organoleptic perception of aliments. Therefore, accurate analysis of VOC is essential, and a need for new analytical methods is witnessed for rapid on‐site detection without complex sample preparation. Surface‐Enhanced Raman Spectroscopy (SERS) offers a rapidly developing versatile analytical platform for the portable detection of chemical species. Nonetheless, the need for efficient docking of target analytes at the metallic surface significantly narrows the applicability of SERS. This limitation can be circumvented by interfacing the sensor surface with Metal–Organic Frameworks (MOF). These materials featuring chemical and structural versatility can efficiently pre‐concentrate low molecular weight species such as VOC through their ordered porous structure. This review presents recent trends in the development of MOF‐based SERS substrates with a focus on elucidating respective design rules for maximizing analytical performance. An overview of the status of the detection of harmful VOC is discussed in the context of industrial and environmental monitoring. In addition, a survey of the analysis of VOC biomarkers for medical diagnosis and emerging applications in aroma and flavor profiling is included.
The application of electrically conductive 1D coordination polymers (1D CPs) in nanoelectronic molecular recognition is theoretically promising yet rarely explored due to the challenges in their synthesis and optimization of electrical properties. In this regard, two tetrathiafulvalene‐based 1D CPs, namely [Co( m ‐H 2 TTFTB)(DMF) 2 (H 2 O)] n (Co‐ m ‐TTFTB), and {[Ni( m ‐H 2 TTFTB)(CH 3 CH 2 OH) 1.5 (H 2 O) 1.5 ]·(H 2 O) 0.5 } n (Ni‐ m ‐TTFTB) are successfully constructed. The shorter S···S contacts between the [M(solvent) 3 ( m ‐H 2 TTFTB)] n chains contribute to a significant improvement in their electrical conductivities. The powder X‐ray diffraction (PXRD) under different organic solvents reveals the flexible and dynamic structural characteristic of M‐ m ‐TTFTB, which, combined with the 1D morphology, lead to their excellent performance for sensitive detection of volatile organic compounds. Co‐ m ‐TTFTB achieves a limit of detection for ethanol vapor down to 0.5 ppm, which is superior to the state‐of‐the‐art chemiresistive sensors based on metal‐organic frameworks or organic polymers at room temperature. In situ diffuse reflectance infrared Fourier transform spectroscopy, PXRD measurements and density functional theory calculations reveal the molecular insertion sensing mechanism and the corresponding structure–function relationship. This work expands the applicable scenario of 1D CPs and opens a new realm of 1D CP‐based nanoelectronic sensors for highly sensitive room temperature gas detection.
In recent years, there has been a lot of interest in using nanotechnology in medicine to diagnose and cure various infectious diseases. Although the precise mechanism of action is frequently challenged, many nanosized materials have been extensively explored for this purpose, using their innately unique features. Their functionality has also been enhanced by the addition of various coatings, such as those that increase chemical stability and stealth properties or contain targeting agents that lessen off-target effects while producing effective "smart" nanoplatforms for the early detection, treatment, and possibly resolution of diseases.
This book aims to compile research and review articles that concentrate on the synthesis, characterization, and applications of nanomaterials, such as nanoparticles, with a focus on investigating novel ways to improve their properties and create new efficient diagnostic, therapeutic, or theranostic approaches with a clear understanding of how they work.
A portable and noninvasive sensor presents an innovative way to measure inflammation biomarkers in exhaled breath condensate (EBC). The current work involves creating a close bipolar electro sensor based analytical...
Biosensors are analytical tools for monitoring various parameters related to living organisms, such as humans and plants. Liquid metals (LMs) have emerged as a promising new material for biosensing applications in recent years. LMs have attractive physical and chemical properties such as deformability, high thermal and electrical conductivity, low volatility, and low viscosity. LM‐based biosensors represent a new strategy in biosensing particularly for wearable and real‐time sensing. While early demonstrations of LM biosensors focus on monitoring physical parameters such as strain, motion, and temperature, recent examples show LM can be an excellent sensing material for biochemical and biomolecular detection as well. In this review, the recent progress of LM‐based biosensors for personalized healthcare and disease monitoring via both physical and biochemical signaling is survey. It is started with a brief introduction of the fundamentals of biosensors and LMs, followed by a discussion of different mechanisms by which LM can transduce biological or physiological signals. Next, it is reviewed example LM‐based biosensors that have been used in real biological systems, ranging from real‐time on‐skin physiological monitoring to target‐specific biochemical detection. Finally, the challenges and future directions of LM‐integrated biosensor platforms is discussed.
Cardiac monitoring after heart surgeries is crucial for health maintenance and detecting postoperative complications early. However, current methods like rigid implants have limitations, as they require performing second complex surgeries for removal, increasing infection and inflammation risks, thus prompting research for improved sensing monitoring technologies. Herein, we introduce a nanosensor platform that is biodegradable, biocompatible, and integrated with multifunctions, suitable for use as implants for cardiac monitoring. The device has two electrochemical biosensors for sensing lactic acid and pH as well as a pressure sensor and a chemiresistor array for detecting volatile organic compounds. Its biocompatibility with myocytes has been tested in vitro, and its biodegradability and sensing function have been proven with ex vivo experiments using a three-dimensional (3D)-printed heart model and 3D-printed cardiac tissue patches. Moreover, an artificial intelligence-based predictive model was designed to fuse sensor data for more precise health assessment, making it a suitable candidate for clinical use. This sensing platform promises impactful applications in the realm of cardiac patient care, laying the foundation for advanced life-saving developments.
Integration and synergy of the unique functions of different components have been developed into one of the most convenient and effective ways to construct the composite advanced materials with collective properties and improved performances. In this work, the mace-like tetrathiafulvalene-tetracyanoquinodimethane (TTF-TCNQ)/HKUST-1 composite structures with single single-crystalline TTF-TCNQ submicrorods covered by ordered HKUST-1 nanosheet arrays were successfully constructed by an efficient TTF-TCNQ seed-mediated growth approach. Impressively, thanks to the synergetic and complementary effects between TTF-TCNQ and HKUST-1, the sensors based on such mace-like TTF-TCNQ/HKUST-1 composite structures not only displayed an experimental detection limit of 10 part per billion (ppb) for NO2 detection, but also exhibited outstanding selectivity even if the concentration of the interfering gases was 10 times that of NO2. Meanwhile, good reproducibility and rapid response were also achieved. This work opens the avenue for creation of novel high-performance sensing materials for application in gas sensing.
Although sensor technologies have allowed us to outperform the human senses of sight, hearing, and touch, the development of artificial noses is significantly behind their biological counterparts. This largely stems from the sophistication of natural olfaction, which relies on both fluid dynamics within the nasal anatomy and the response patterns of hundreds to thousands of unique molecular-scale receptors. We designed a sensing approach to identify volatiles inspired by the fluid dynamics of the nose, allowing us to extract information from a single sensor (here, the reflectance spectra from a mesoporous one-dimensional photonic crystal) rather than relying on a large sensor array. By accentuating differences in the nonequilibrium mass-transport dynamics of vapors and training a machine learning algorithm on the sensor output, we clearly identified polar and nonpolar volatile compounds, determined the mixing ratios of binary mixtures, and accurately predicted the boiling point, flash point, vapor pressure, and viscosity of a number of volatile liquids, including several that had not been used for training the model. We further implemented a bioinspired active sniffing approach, in which the analyte delivery was performed in well-controlled 'inhale-exhale' sequences, enabling an additional modality of differentiation and reducing the duration of data collection and analysis to seconds. Our results outline a strategy to build accurate and rapid artificial noses for volatile compounds that can provide useful information such as the composition and physical properties of chemicals, and can be applied in a variety of fields, including disease diagnosis, hazardous waste management, and healthy building monitoring.
The different immune system cells communicate and coordinate a response using a complex and evolved language of cytokines and chemokines. These cellular interactions carry out multiple functions in distinct cell types with numerous developmental outcomes. Despite the plethora of different cytokines and their cognate receptors, there is a restricted number of signal transducers and activators to control immune responses. Herein, we report on a new class of immunomodulatory signaling molecules based on volatile molecules (VMs, namely, volatile organic compounds [VOCs]), by which they can affect and/or control immune cell behavior and transcriptomic profile without any physical contact with other cells. The study demonstrates the role of VMs by analyzing non‐contact cell communication between normal and cancerous lung cells and U937 monocytes, which are key players in the tumor microenvironment. Integrated transcriptome and proteome analyses showed the suggested regulatory role of VMs released from normal and cancer cells on neighboring monocytes in several molecular pathways, including PI3K/AKT, PPAR, and HIF‐1. Presented data provide an initial platform for a new class of immunomodulatory molecules that can potentially mirror the genomic and proteomic profile of cells, thereby paving the way toward non‐invasive immunomonitoring.
Although great achievements have been made in the study of artificial enzymes, the design of nanozymes with high catalytic activities of natural enzymes and the further establishment of sensitive biosensors still remain challenging. Here, two nanozymes, i.e., ZnCoFe three-atom nanozyme (TAzyme) and Sn single-atom nanozyme (SAzyme)/Ti3C2Tx, are developed, which show peroxidase-like catalytic activities by catalyzing the reaction of hydrogen peroxide (H2O2), 4-aminoantipyrine (4-AAP), and phenolic acids to generate colorimetric reactions. The involvement of different phenolic acids leads to the generation of different color products. These subtle color-variation profiles between these phenolic acids prompt us to exploit an electronic tongue based on the two nanozymes to distinguish phenolic acids. Data interpretation by the pattern recognition method, such as linear discriminant analysis (LDA), displays good clustering separation of six different phenolic acids at concentrations of 0.1 μM to 1 mM, validating the effectiveness of the colorimetric nanozyme sensor array.
Coronavirus disease 2019 (COVID-19) vaccines can protect people from the infection; however, the action mechanism of vaccine-mediated metabolism remains unclear. Herein, we performed breath tests in COVID-19 vaccinees that revealed metabolic reprogramming induced by protective immune responses. In total, 204 breath samples were obtained from COVID-19 vaccinees and non-vaccinated controls, wherein numerous volatile organic compounds (VOCs) were detected by comprehensive two-dimensional gas chromatography and time-of-flight mass spectrometry system. Subsequently, 12 VOCs were selected as biomarkers to construct a signature panel using alveolar gradients and machine learning-based procedure. The signature panel could distinguish vaccinees from control group with a high prediction performance (AUC, 0.9953; accuracy, 94.42%). The metabolic pathways of these biomarkers indicated that the host-pathogen interactions enhanced enzymatic activity and microbial metabolism in the liver, lung, and gut, potentially constituting the dominant action mechanism of vaccine-driven metabolic regulation. Thus, our findings of this study highlight the potential of measuring exhaled VOCs as rapid, non-invasive biomarkers of viral infections. Furthermore, breathomics appears as an alternative for safety evaluation of biological agents and disease diagnosis.
Liquid biopsy is seen as a prospective tool for cancer screening and tracking. However, the difficulty lies in effectively sieving, isolating, and overseeing cancer biomarkers from the backdrop of multiple disrupting cells and substances. The current study reports on the ability to perform liquid biopsy without the need to physically filter and/or isolate the cancer cells per se. This has been achieved through the detection and classification of volatile organic compounds (VOCs) emitted from the cancer cells found in the headspace of blood or urine samples or a combined data set of both. Spectrometric analysis shows that blood and urine contain complementary or overlapping VOC information on kidney cancer, gastric cancer, lung cancer, and fibrogastroscopy subjects. Based on this information, a nanomaterial-based chemical sensor array in conjugation with machine learning as well as data fusion of the signals achieved was carried out on various body fluids to assess the VOC profiles of cancer. The detection of VOC patterns by either Gas Chromatography-Mass Spectrometry (GC-MS) analysis or our sensor array achieved >90% accuracy, >80% sensitivity, and >80% specificity in different binary classification tasks. The hybrid approach, namely, analyzing the VOC datasets of blood and urine together, contributes an additional discrimination ability to the improvement (>3%) of the model's accuracy. The contribution of the hybrid approach for an additional discrimination ability to the improvement of the model's accuracy is examined and reported.
Investigation and evolution in the involved sciences at the molecular or atomic level is the demand of the day under the discipline of nanoscience or nanotechnology, with massive impact on almost all regions of human health and conditioning, including various medical domains such as clinical diagnoses, pharmacological investigations, and additional resistant methods. The domain of nano-dentistry has appeared due to the assorted dental applications and consequences of nanotechnology. This chapter first outlines classifications and categories of nanomaterials established on their source, biochemical arrangement, resources, and measurements. The basic effects of value conversion at the nanoscale and the multiple improved and valuable effects of fabricated nanomaterials, such as incarceration effects, texture influences, mechanical impacts, structural developments, thermal developments, optical effects, magnetic effects, and dental application, are also described. In the final section, we looked at in vivo, in vitro, and the effects of nanomaterials.
Endogenous or exogenous process byproducts include a wide range of chemicals, which can be used as promising candidate biomarkers for systemic diseases. Among them, Volatile Organic Compounds (VOCs) expressed in biological fluids could be evaluated through non-invasive techniques for the diagnosis and follow-up of a pathological condition (e.g., inflammatory process, neoplasia, etc.). Among VOCs contained in biological fluids, propionic and succinic acids are involved in important inflammatory processes. The development of a reliable, non-invasive sensor for the rapid quantification of VOCs is thus a topic of interest, especially for the screening of large populations. To this end, we investigated synthetic zeolite as a nanoporous adsorbing layer for the development of a VOCs sensor. Zeolite type 4A has been used as it provides a large surface/area ratio, a well-defined porosity, and considerable ion-exchange capabilities. A detection system based on a photoionization system has been investigated. The quantification of VOCs was evaluated by analyzing the emission profiles during the desorption process, which is strongly influenced by the environmental parameters such as temperature. Results evidenced that the joint use of a zeolite layer and a photoionization system is able to detect and quantify the presence of propionic acid respect to the succinic, since the latter is poorly physically adsorbed in the layer. The overall device is thus able to detect and quantify specific VOCs trapped inside the zeolite layer with a linear relation between the desorbed molecules and the sample concentration.
Rapid progress in the synthesis and fundamental understanding of 1D and 2D materials have solicited the incorporation of these nanomaterials into sensor architectures, especially field effect transistors (FETs), for the monitoring of gas and vapor in environmental, food quality, and healthcare applications. Yet, several challenges have remained unaddressed toward the fabrication of 1D and 2D FET gas sensors for real‐field applications, which are related to properties, synthesis, and integration of 1D and 2D materials into the transistor architecture. This review paper encompasses the whole assortment of 1D—i.e., metal oxide semiconductors (MOXs), silicon nanowires (SiNWs), carbon nanotubes (CNTs)—and 2D—i.e., graphene, transition metal dichalcogenides (TMD), phosphorene—materials used in FET gas sensors, critically dissecting how the material synthesis, surface functionalization, and transistor fabrication impact on electrical versus sensing properties of these devices. Eventually, pros and cons of 1D and 2D FETs for gas and vapor sensing applications are discussed, pointing out weakness and highlighting future directions.
Abstract: Access to point-of-care (POC) diagnostics services is essential for ensuring rapid disease
diagnosis, management, control, and surveillance. POC testing services can improve access to
healthcare especially where healthcare infrastructure is weak and access to quality and timely
medical care is a challenge. Improving the accessibility and efficiency of POC diagnostics services,
particularly in resource-limited settings, may be a promising route to improving healthcare outcomes.
In this review, the accessibility of POC testing is defined as the distance/proximity to the nearest
healthcare facility for POC diagnostics service. This review provides an overview of the impact of
POC diagnostics on healthcare outcomes in low- and middle-income countries (LMICs) and factors
contributing to the accessibility of POC testing services in LMICs, focusing on characteristics of the
supply chain management and quality systems management, characteristics of the geographical
location, health infrastructure, and an enabling policy framework for POC diagnostics services.
Barriers and challenges related to the accessibility of POC diagnostics in LMICs were also discussed.
Bearing in mind the reported barriers and challenges as well as the disease epidemiology in LMICs,
we propose a lean and agile supply chain management framework for improving the accessibility
and efficiency of POC diagnostics services in these settings.
Love-wave gas sensors based on surface functionalized iron oxide nanoparticles has been developed in this research. Amino-terminated iron oxide nanoparticles were deposited, by a spin coating technique, onto the surface of Love-wave sensors, as a very reproducible gas-sensing layer. The gases tested were organic solvents, such as butanol, isopropanol, toluene and xylene, for a wide and low concentration range, obtaining great responses, fast response times of a few minutes (the time at which the device produced a signal change equal to 90%), good reproducibilities, and different responses for each detected solvent. The estimated limits of detection obtained have been very low for each detected compound, about 1 ppm for butanol, 12 ppm for isopropanol, 3 ppm for toluene and 0.5 ppm for xylene. Therefore, it is demonstrated that this type of acoustic wave sensor, with surface amino-functionalized nanoparticles, is a good alternative to those ones functionalized with metal nanoparticles, which result very expensive sensors to achieve worse results.
Arrays with polymer-coated acoustic sensors, such as surface acoustic wave (SAW) and surface transverse wave (STW) sensors, have successfully been applied for a variety of gas sensing applications. However, the stability of the sensors’ polymer coatings over a longer period of use has hardly been investigated. We used an array of eight STW resonator sensors coated with different polymers. This sensor array was used at semi-annual intervals for a three-year period to detect organic solvent vapors of three different chemical classes: a halogenated hydrocarbon (chloroform), an aliphatic hydrocarbon (octane), and an aromatic hydrocarbon (xylene). The sensor signals were evaluated with regard to absolute signal shifts and normalized signal shifts leading to signal patterns characteristic of the respective solvent vapors. No significant time-related changes of sensor signals or signal patterns were observed, i.e., the polymer coatings kept their performance during the course of the study. Therefore, the polymer-coated STW sensors proved to be robust devices which can be used for detecting organic solvent vapors both qualitatively and quantitatively for several years.
Exhaled breath is a body secretion, and the sampling process of this is simple and cost effective. It can be non-invasively collected for diagnostic procedures. Variations in the chemical composition of exhaled breath resulting from gaseous exchange in the extensive capillary network of the body are proposed to be associated with pathophysiological changes. In light of the foreseeable potential of exhaled breath as a diagnostic specimen, we used gas chromatography and mass spectrometry (GC-MS) to study the chemical compounds present in exhaled breath samples from patients with Alzheimer’s disease (AD), Parkinson’s disease (PD), and from healthy individuals as a control group. In addition, we also designed and developed a chemical-based exhaled breath sensor system to examine the distribution pattern in the patient and control groups. The results of our study showed that several chemical compounds, such as 1-phenantherol and ethyl 3-cyano-2,3-bis (2,5,-dimethyl-3-thienyl)-acrylate, had a higher percentage area in the AD group than in the PD and control groups. These results may indicate an association of these chemical components in exhaled breath with the progression of disease. In addition, in-house fabricated exhaled breath sensor systems, containing several types of gas sensors, showed significant differences in terms of the normalized response of the sensitivity characteristics between the patient and control groups. A subsequent clustering analysis was able to distinguish between the AD patients, PD patients, and healthy individuals using principal component analysis, Sammon’s mapping, and a combination of both methods, in particular when using the exhaled breath sensor array system A consisting of eight sensors. With this in mind, the exhaled breath sensor system could provide alternative option for diagnosis and be applied as a useful, effective tool for the screening and diagnosis of AD in the near future.
Background
Early detection of lung cancer (LC) has been well established as a significant key point in patient survival and prognosis. New highly sensitive nanoarray sensors for exhaled Volatile Organic Compounds (VOCs) have been developed and coupled with powerful statistical programs may be used when diseases such as LC are suspected. Detection of genetic aberration mutation by nanoarray sensors is the next target.
Methods
Breath samples were taken from patients who were evaluated for suspicious pulmonary lesions. Patients were classified as those with benign nodules, LC patients with or without the EGFR mutation, and according to their smoking status. 'Breath-prints' were recognized by nanomaterial based sensor array (NA-NOSE), and pattern recognition methods were used.
Results
A total of 119 patients participated in this study, 30 patients with benign nodules and 89 LC patients (n=16 with early and n=73 with advanced disease). . LC patients who harbor the EGFR mutation (n=19) could be discriminated from wild-type (n=34) with an accuracy of 83%, a sensitivity of 79% and a specificity of 85%. Discrimination of early LC from benign nodules had 87% accuracy and positive and negative predictive values (PPV and NPV) of 87.7 and 87.5% respectively. Moderate discrimination (accuracy of 76%) was found between LC of heavy smokers and never or distant past light smokers.
Conclusion
Breath analysis could discriminate LC patients who harbor the EGFR mutation from wild type and those with benign pulmonary nodules from early LC patients. Positive 'breath-print' for the EGFR mutation may be used in treatment decisions if tissue sampling does not provide adequate material for definitive mutation analysis.
Controlling the droplet shape and the corresponding deposition patterns is pivotal in a wide range of processes and applications based on surface phenomena, such as self-assembly of different types of nanomaterials and fabrication of functional electronic devices. In this paper we study different flow regimes and deposition patterns from volatile sessile droplets and droplets sliding over inclined solid substrates. The directionality and intensity of the Marangoni flow was controlled by vapor composition in a sealed chamber enclosing the evaporating droplets. Two types of volatile droplets are investigated: single component droplets and binary solution droplets. Binary solution droplets can exhibit either inward or outward Marangoni soluto-capillary flow, depending on a surface tension dependence on the concentration of the fast evaporating component. We carried out a detailed experimental study of the micro-rivulet (μ-R) regime in different binary solutions. The μ-R formation in a certain range of Ca proved to be a universal phenomenon subject to the occurrence of inward Marangoni flow. We propose a simplified mathematical model for the shape of μ-R based on the lubrication approximation. The resulting μ-R profile shows a good agreement with the experimental results.
Abstract
Purpose– This review paper aims to focus on recent advances of carbon nanotubes (CNTs) to produce gas sensors. Gas sensors are widely used
for monitoring hazardous gas leakages and emissions in the industry, households and other areas. For better safety and a healthy environment, it
is highly desirable to have gas sensors with higher accuracy and enhanced sensing features.
Design/methodology/approach– In this review, the authors focus on recent contributions of CNTs to the technology for developing different types
of gas sensors. The design, fabrication process and sensing mechanism of each gas sensor are summarized, together with their advantages and
disadvantages.
Findings– Nowadays, CNTs are well-known materials which have attracted a significant amount of attention owing to their excellent electrical,
electronic and mechanical properties. On exposure to various gases, their properties allow the detection of gases using different methods. Therefore,
over recent years, researchers have developed several different types of gas sensors along with other types of sensors for temperature, strain,
pressure, etc.
Originality/value– The main purpose of this review is to introduce CNTs as candidates for future research in the field of gas sensing applications
and to focus on current technical challenges associated with CNT-based gas sensors
The analysis of volatile organic compounds (VOCs) emanating from biological samples appears as one of the most promising approaches in metabolomics for the study of diseases, namely cancer. In fact, it offers advantages, such as non-invasiveness and robustness for high-throughput applications. The purpose of this work was to study the urinary volatile metabolic profile of patients with renal cell carcinoma (RCC) (n = 30) and controls (n = 37) with the aim of identifying a potential specific urinary volatile pattern as a non-invasive strategy to detect RCC. Moreover, the effect of some confounding factors such as age, gender, smoking habits and body mass index was evaluated as well as the ability of urinary VOCs to discriminate RCC subtypes and stages. A headspace solid-phase microextraction/gas chromatography–mass spectrometry-based method was performed, followed by multivariate data analysis. A variable selection method was applied to reduce the impact of potential redundant and noisy chromatographic variables, and all models were validated by Monte Carlo cross-validation and permutation tests. Regarding the effect of RCC on the urine VOCs composition, a panel of 21 VOCs descriptive of RCC was defined, capable of discriminating RCC patients from controls in principal component analysis. Discriminant VOCs were further individually validated in two independent samples sets (nine RCC patients and 12 controls, seven RCC patients with diabetes mellitus type 2) by univariate statistical analysis. Two VOCs were found consistently and significantly altered between RCC and controls (2-oxopropanal and, according to identification using NIST14, 2,5,8-trimethyl-1,2,3,4-tetrahydronaphthalene-1-ol), strongly suggesting enhanced potential as RCC biomarkers. Gender, smoking habits and body mass index showed negligible and age-only minimal effects on the urinary VOCs, compared to the deviations resultant from the disease. Moreover, in this cohort, the urinary volatilome did not show ability to discriminate RCC stages and histological subtypes. The results validated the value of urinary volatilome for the detection of RCC and advanced with the identification of potential RCC urinary biomarkers.
Skin-based wearable devices have a great potential that could result in a revolutionary approach to health monitoring and diagnosing disease. With continued innovation and intensive attention to the materials and fabrication technologies, development of these healthcare devices is progressively encouraged. This article gives a concise, although admittedly non-exhaustive, didactic review of some of the main concepts and approaches related to recent advances and developments in the scope of skin-based wearable devices (e.g. temperature, strain, biomarker-analysis werable devices, etc.), with an emphasis on emerging materials and fabrication techniques in the relevant fields. To give a comprehensive statement, part of the review presents and discusses different aspects of these advanced materials, such as the sensitivity, biocompatibility and durability as well as the major approaches proposed for enhancing their chemical and physical properties. A complementary section of the review linking these advanced materials with wearable device technologies is particularly specified. Some of the strong and weak points in development of each wearable material/device are highlighted and criticized. Several ideas regarding further improvement of skin-based wearable devices are also discussed.
There is accumulating evidence in support of the significant improvement in survival rates and clinical outcomes when pulmonary arterial hypertension (PAH) is diagnosed at early stages. Nevertheless, it remains a major clinical challenge and the outcomes are dependent on invasive right heart catheterisation.
Resulting from pathophysiological processes and detectable in exhaled breath, volatile organic compounds (VOCs) have been proposed as noninvasive biomarkers for PAH. Studies have confirmed significant alterations of the exhaled VOCs among PAH patients when compared to controls and/or patients with other respiratory diseases. This suggests exhaled breath analysis as a potential noninvasive medical application in the field of PAH.
In this article, we review and discuss the progress made so far in the field of exhaled volatolomics (the omics of VOCs) as a potential noninvasive diagnostics of PAH. In addition, we propose a model including possible biochemical pathways on the level of the remodelled artery, in which specific VOCs could be detectable in exhaled breath during the early phases of PAH. We debate the different analytical approaches used and recommend a diagram including a “bottom–top” strategy, from basic to translational studies, required for promoting the field.
To achieve the rational design of nanostructures for superior gas sensors, the ultrasmall nanoparticles (NPs) loaded on ternary metal oxide (TMO) hollow spheres (HS) were synthesized by using the polystyrene (PS) sphere template and bimetallic metal-organic framework (BM-MOFs) mold. The zinc and cobalt based zeolite imidazole frameworks (BM-ZIFs) encapsulating ultrasmall Pd NPs (2–3 nm) were assembled on PS spheres at room temperature. After calcination at 450 °C, these nanoscale Pd particles were effectively infiltrated on the surface of ZnO/ZnCo2O4 HSs. In addition, the heterojunctions of Pd-ZnO, Pd-ZnCo2O4, and ZnO-ZnCo2O4 were formed on each phase. The synthesized Pd-ZnO/ZnCo2O4 HSs exhibited extremely high selectivity toward acetone gas with notable sensitivity (S = 69% to 5 ppm at 250 °C). The results demonstrate that MOF driven ultrasmall catalyst loaded TMO HSs were highly effective platform for high performance chemical gas sensors.
Breath acetone serves as a biomarker for diabetes. This article reports 1-butyl-3-methylimidazolium tetrafluoroborate ([bmim][BF4]), a type of room temperature ionic liquid (RTIL), as a selective sensing material for acetone. The RTIL sensing layer was coated on a quartz crystal microbalance (QCM) for detection. The sensing mechanism is based on a decrease in viscosity and density of the [bmim][BF4] film due to the solubilization of acetone leading to a positive frequency shift in the QCM. Acetone was detected with a linear range from 7.05 to 750 ppmv. Sensitivity and limit of detection were found to be 3.49 Hz/ppmv and 5.0 ppmv, respectively. The [bmim][BF4]-modified QCM sensor demonstrated anti-interference ability to commonly found volatile organic compounds in breath, e.g., isoprene, 1,2-pentadiene, d-limonene, and dl-limonene. This technology is useful for applications in non-invasive early diabetic diagnosis.
A free-standing, flexible, and semi-transparent MoO3 nanopaper was fabricated using ultralong MoO3 nanobelts (length ∼ 200 μm; width 200–400 nm), and its gas-sensing characteristics were investigated. The sensor exhibited high responses (resistance ratio) of 49 to 5 parts per million (ppm) hydrogen sulfide (H2S) at 250 °C and 121 to 5 ppm trimethylamine (TMA) at 325 °C with excellent gas selectivity, demonstrating its dual function for gas detection. Moreover, the sensor showed promising potential for the all-in-one detection of three representative offensive odors (TMA, H2S, and NH3) simply by tuning of the sensing temperature. This particular performance is attributed to the high chemical affinity of MoO3 to H2S and the acid–base interaction between basic TMA/NH3 and acidic MoO3. The mechanism underlying the control of gas selectivity by modulating the sensor temperature was investigated by Diffuse Reflectance Infrared Fourier Transform (DRIFT) measurements.
Graphene and its derivatives have become the most explored materials since Novoselov and Geim (Nobel Prize winners for Physics in 2010) achieved its isolation in 2004. The exceptional properties of graphene have attracted the attention of the scientific community from different research fields, generating high impact not only in scientific journals, but also in general-interest newspapers. Optical fibre sensing is one of the many fields that can benefit from the use of these new materials, combining the amazing morphological, chemical, optical and electrical features of graphene with the advantages that optical fibre offers over other sensing strategies. In this document, a review of the current state of the art for optical fibre sensors based on graphene materials is presented.
Multi-parametric sensing platforms offer the possibility to measure simultaneously several stimuli, and potentially to differentiate between the different signals. They have advantages in fields that include wearable systems, humanoid robotics, structural health monitoring and precision agriculture, since a complex stimuli from the environment is usually an integrated component in these examples. In the current progress report, we present and discuss new avenues in nanoparticle-based multi-parametric sensing platforms for the detection, classification and separation of common stimuli, e.g., temperature, humidity, strain/pressure and volatile organic compounds (VOCs). New data involving multi-parametric sensing with nanoparticle-based sensors are given for each topic. Future prospects are discussed.
In this work, a novel composed morphology of iron oxide micro-structures covered with very thin nanowires (NW) with diameter of 15 – 50 nm have been presented in premiere. By oxidizing metallic Fe micro-particles at 255 °C for 12 h and 24 h, dense iron oxide NW networks bridging pre-patterned Au/Cr pads were obtained. XPS studies reveal formation of α-Fe2O3 and Fe3O4 on the surface and it was confirmed by detailed HRTEM and SAED investigations that NWs are single phase α-Fe2O3 and some domains of single phase Fe3O4. Localized synthesis of such nano- and micro-particles directly on sensor platform/structure at 255 °C for 24 h and re-oxidation at 650 °C for 0.2-2 h, yield in highly performance and reliable detection of acetone vapour with fast response and recovery times. High repeatability and complete recovery of electrical resistance to initial baseline after exposure to analyte gas, demonstrates excellent potential for fabrication of reliable and robust nano- and micro-sensor structures for biomedical and cosmetic applications, since acetone being extremely inflammable it is important to rapidly detect leaks of acetone vapour to prevent explosions or flash fire. The p-type behavior of n-type α-Fe2O3 and half-metal Fe3O4 could be a consequence of interesting/new electrical and conduction properties of mixed phases of iron oxides. First nanosensors on single α-Fe2O3 nanowire were fabricated and studied showing excellent performances. Several nanodevices based on a single α-Fe2O3 NW with different diameters showing an increase in acetone response by decrease of diameter were developed. Our facile technological approach enables this nanomaterial as candidate for a range of applications in the field of nanoelectronics such as nanosensors and biomedicine devices, especially for breath analysis in the treatment of diabetes patients.
Objectives:
We determined the performance of a sensor array (an electronic nose) made of 8 metalloporphyrins coated quartz microbalances sensors for the diagnosis and prognosis of pulmonary tuberculosis (TB) using exhaled breath samples.
Methods:
TB cases and healthy controls were prospectively enrolled. Signals from volatile organic compounds (VOCs) in breath samples were measured at days 0, 2, 7, 14, and 30 of TB therapy and correlated with clinical and microbiological measurements.
Results:
51 pulmonary TB cases and 20 healthy HIV-uninfected controls were enrolled in the study. 31 (61%) of the 51 pulmonary TB cases were coinfected with HIV. At day 0 (before TB treatment initiation) the sensitivity of our device was estimated at 94.1% (95% confidence interval [CI], 83.8-98.8%) and specificity was 90.0% (95% CI, 68.3-98.8%) for distinguishing TB cases from controls. Time-dependent changes in the breath signals were identified as time on TB treatment progressed. Time-dependent signal changes were more pronounced among HIV-uninfected patients.
Conclusion:
The identification of VOCs signals in breath samples using a sensor array achieved high sensitivity and specificity for the diagnosis of TB and allowed following signal changes during TB treatment.
Capabilities in health monitoring enabled by capture and quantitative chemical analysis of sweat could complement, or potentially obviate the need for, approaches based on sporadic assessment of blood samples. Established sweat monitoring technologies use simple fabric swatches and are limited to basic analysis in controlled laboratory or hospital settings. We present a collection of materials and device designs for soft, flexible, and stretchable microfluidic systems, including embodiments that integrate wireless communication electronics, which can intimately and robustly bond to the surface of the skin without chemical and mechanical irritation. This integration defines access points for a small set of sweat glands such that perspiration spontaneously initiates routing of sweat through a microfluidic network and set of reservoirs. Embedded chemical analyses respond in colorimetric fashion to markers such as chloride and hydronium ions, glucose, and lactate. Wireless interfaces to digital image capture hardware serve as a means for quantitation. Human studies demonstrated the functionality of this microfluidic device during fitness cycling in a controlled environment and during long-distance bicycle racing in arid, outdoor conditions. The results include quantitative values for sweat rate, total sweat loss, pH, and concentration of chloride and lactate.
Semiconductor nanowires (NWs), in particular Si NWs, have attracted much attention in the last decade for their unique electronic properties and potential applications in several emerging areas. With the introduction of heterostructures (HSs) on NWs, new functionalities are obtained and the device performance is improved significantly in many cases. Due to the easy fabrication techniques, excellent optoelectronic properties and compatibility of forming HSs with different inorganic/organic materials, Si NW HSs have been utilized in various configurations and device architectures. Herein, we review the recent developments in Si NW HS-based devices including the fabrication techniques, properties (e.g., light emitting, antireflective, photocatalytic, electrical, photovoltaic, sensing etc) and related emerging applications in energy generation, conversion, storage, and environmental cleaning and monitoring. In particular, recent advances in Si NW HS-based solar photovoltaics, light-emitting devices, thermoelectrics, Li-ion batteries, supercapacitors, hydrogen generation, artificial photosynthesis, photocatalytic degradation of organic dyes in water treatment, chemical and gas sensors, biomolecular sensors for microbial monitoring etc have been addressed in detail. The problems and challenges in utilizing Si NW HSs in device applications and the key parameters to improve the device performance are pointed out. The recent trends in the commercial applications of Si NW HS-based devices and future outlook of the field are presented at the end.
Rare genetic diseases collectively impact a significant portion of the world's population. For many diseases there is limited information available, and clinicians can find difficulty in differentiating between clinically similar conditions. This leads to problems in genetic counseling and patient treatment. The biomedical market is affected because pharmaceutical and biotechnology industries do not see advantages in addressing rare disease treatments, or because the cost of the treatments is too high. By contrast, technological advances including DNA sequencing and analysis, together with computer-aided tools and online resources, are allowing a more thorough understanding of rare disorders. Here, we discuss how a collection of various types of information together with the use of new technologies is facilitating diagnosis and, consequently, treatment of rare diseases.
This study describes two biosniffers to determine breath acetone and isopropanol (IPA) levels and applies them for breath measurement in healthy subjects and diabetic patients. Secondary alcohol dehydrogenase (S-ADH) can reduce acetone and oxidize nicotinamide adenine dinucleotide (NADH to NAD⁺) in a weak acid environment. NADH can be excited by 340 nm excitation lights and subsequently emit 490 nm fluorescence. Therefore, acetone can be measured by the decrease in NADH fluorescence intensity. S-ADH can also oxidize IPA and reduce NAD⁺ to NADH when it is in an alkaline environment. Thus, IPA can be detected by the increase of fluorescence. The developed biosniffers show rapid response, high sensitivity and high selectivity. The breath acetone and IPA analysis in healthy subjects shows that the mean values were 750.0 ± 434.4 ppb and 15.4 ± 11.3 ppb. Both acetone and IPA did not show a statistical difference among different genders and ages. The breath acetone analysis for diabetic patients shows a mean value of 1207.7 ± 689.5 ppb, which was higher than that of healthy subjects (p < 1 × 10–6). In particularly, type-1 diabetic (T1D) patients exhaled a much higher concentration of acetone than type-2 diabetic (T2D) patients (p < 0.01). The breath IPA also had a higher concentration in diabetic patients (23.1 ± 20.1 ppb, p < 0.01), but only T2D patients presented a statistical difference (23.9 ± 21.3 ppb, p < 0.01). These findings are worthwhile in the study of breath biomarkers for diabetes mellitus diagnosis. Additionally, the developed biosniffers provide a new technique for volatolomics research.
Surface acoustic wave (SAW) devices provide a convenient platform for the realization of sensors in the present decade. 99.4MHz SAW resonator has been fabricated over the ST cut quartz. Subsequently PZT thin film has been deposited by pulsed laser deposition technique as a sensing layer over the fabricated SAW resonator. Shift in resonance frequency was measured precisely for varying concentration of NO2 gas. The calibration curve was found to be linear having a sensitivity of 9.6Hz/ppm. The fabricated sensor is advantageous for its room temperature, handheld and wireless sensing.
Early diagnosis of Parkinson’s disease (PD) is of great importance due its progressive phenotype. Neuroprotective drugs could potentially slow down disease progression if used at early stages. Previously, we have reported an altered content of volatile organic compounds (VOCs) in the breath of rats following a 50% reduction in striatal dopamine (DA) content induced by 6-hydroxydopamine. We now report on the difference in the breath-print and content of VOCs between rats with mild and severe lesions of DA neurons, serotonergic neuronal lesions, and transgenic (Tg) rats carrying the PD-producing A53T mutation of the SNCA (alpha-synuclein) gene. The Tg rats had an increased content of 3-octen-1-ol and 4-chloro-3-methyl phenol in blood, while in brain tissue, hexanal, hexanol and 2,3-octanedione were present in controls but absent in Tg rats. Levels of 1-heptyl-2-methyl cyclopropane were increased in brain tissue of Tg rats. The data confirm the potential of breath analysis for detection of human- idiosyncratic as well as autosomal dominant PD.
Semiconductor gas sensors using metal oxides, carbon nanotubes, graphene-based materials, and metal chalcogenides have been reviewed from the viewpoint of the sensitive, selective, and reliable detection of exhaled biomarker gases,...
For detection of gases and vapors in complex backgrounds, “classic” analytical instruments are an unavoidable alternative to existing sensors. Recently a new generation of sensors, known as multivariable sensors, emerged with a fundamentally different perspective for sensing to eliminate limitations of existing sensors. In multivariable sensors, a sensing material is designed to have diverse responses to different gases and vapors and is coupled to a multivariable transducer that provides independent outputs to recognize these diverse responses. Data analytics tools provide rejection of interferences and multi-analyte quantitation. This review critically analyses advances of multivariable sensors based on ligand-functionalized metal nanoparticles also known as monolayer-protected nanoparticles (MPNs). These MPN sensing materials distinctively stand out from other sensing materials for multivariable sensors due to their diversity of gas- and vapor-response mechanisms as provided by organic and biological ligands, applicability of these sensing materials for broad classes of gas-phase compounds such as condensable vapors and non-condensable gases, and for several principles of signal transduction in multivariable sensors that result in non-resonant and resonant electrical sensors as well as material- and structure-based photonic sensors. Such features should allow MPN multivariable sensors to be an attractive high value addition to existing analytical instrumentation.
Multiple sclerosis (MS) is the most common chronic neurological disease affecting young adults. MS diagnosis is based on clinical characteristics and confirmed by examination of the cerebrospinal fluids or by magnetic resonance imaging of the brain and/or spinal cord. However, neither of the current diagnostic procedures are adequate as a routine tool to determine disease progression. Thus, diagnostic biomarkers are needed. In the current study, a novel approach that could meet these expectations is presented. The approach is based on non-invasive analysis of volatile organic compounds (VOCs) in breath. Exhaled breath was collected from 204 volunteers, 164 MS and 58 control individuals. Analysis was performed by: gas-chromatography mass-spectrometry (GC-MS) and nanomaterial-based sensors array. Predictive models were derived from the sensors, using Artificial Neural Networks. GC-MS analysis revealed significant differences in VOCs abundance between MS patients and Controls. Sensor data analysis on training sets were able to binary discriminate between MS patients and Controls with accuracies up-to 90%. Blinded sets showed 95% positive predictive value between MS-remission and control and 100% sensitivity with 100% negative predictive value between MS not-treated (NT) and control, and 86% NPV between relapse and control. Possible links between VOC biomarkers and the MS pathogenesis were established. Preliminary results suggest the applicability of a new nanotechnology-based method for MS diagnostics.
Pristine SiO2, TiO2 and composite SiO2-TiO2 films of 200 nm thick were coated on surface of quartz acoustic wave (SAW) sensors with sol-gel and spin coating technique. Their performance and mechanisms for sensing NH3 were systematically investigated. Sensors made with the TiO2 and SiO2-TiO2 films showed positive frequency shifts, whereas SiO2 film exhibits a negative frequency shift to NH3 gas. it is believed that the negative frequency shift was mainly caused by the increase of NH3 mass loading on the sensitive film while the positive frequency shift was associated to the condensation of the hydroxyl groups (-OH) on the film making the film stiffer and lighter, when exposed to NH3 gas. It demonstrated that humidity played a significant factor on the sensing performance. Comparative studies exhibited that the sensor based on the composite SiO2-TiO2 film had a much better sensitivity to NH3 at a low concentration level (1 ppm) with a response of 2 KHz, and also showed fast response and recovery, excellent selectivity, stability and reproducibility.
A Surface Acoustic Wave (SAW) resonator operating at a frequency of 99.50 MHz using piezoelectric ST-cut quartz has been fabricated. The resonator device has been successfully integrated with ZnO sensing layer for detection of NO2 gas. The fabricated sensor device is found to be detecting trace level concentration of NO2 gas (400 ppb to 16 ppm) efficiently and selectively. The ZnO/Quartz SAW sensor is useful for wireless detection of NO2 gas.
Urinary tract infection (UTI) is the most common bacterial infection independent of age. It is also one of the most common causes of hospitalizations for infections among elderly people and the most common indication for antibiotic prescriptions in primary care. Both diagnostics and management of lower and upper urinary tract infections provide challenges in clinical practice due to their high prevalence and recurrence, and worldwide increase of antibiotic resistance. The clinical symptoms of UTI are often uncharacteristic or asymptomatic. The accurate diagnosis and early treatment are crucial due to risk of septicaemia and long-term consequences. Currently the diagnosis of urinary tract infection is based on the presence of clinical symptoms in combination with the results of nitrite strip test indicating the presence of bacteria in urine and semi-quantitative measurement of white blood cells count in urine. Although urine culture is the gold standard in UTI diagnostics it is both time-consuming and costly. Searching for novel biomarkers of UTI has attracted much attention in recent years. The article reviews several promising serum and urine biomarkers of UTI such as leukocyte esterase, C-reactive protein, procalcitonin, interleukins, elastase alpha (1)-proteinase inhibitor, lactofferin, secretory immunoglobulin A, heparin-binding protein, xanthine oxidase, myeloperoxidase, soluble triggering receptor expressed on myeloid cells-1, α-1 microglobulin (α1Mg) and tetrazolium nitroblue test (TNB).
Type 2 diabetes mellitus (T2DM) has become a major health threat worldwide. MicroRNAs (miRNAs) are a group of non-coding RNAs known to regulate various biological processes including the pathogenesis of T2DM. Recent studies have pointed out that specific miRNAs play a critical role in controlling β cell activities and the development of diabetic vascular complications. Their association with the disease pathogenesis and omnipresence in body fluids have made them important players for prognosis, diagnosis and management of T2DM. Owing to the limitations of classical biomarkers of diabetes such as fasting plasma glucose, glycosylated haemoglobin (HbA1c) lack in predicting the risk of development of diabetes complications in a susceptible population. The miRNAs can act as ideal biomarkers for diabetes associated complications. Identification of specific miRNA signatures to detect diabetes and ideally to find out the risk of development of diabetes-associated complications in susceptible population is the essential requirement of the present clinical strategies for controlling diabetes worldwide. In this article, we summarize the potential miRNAs and miRNA signatures involved in the β cell activities and diabetes associated macrovascular and microvascular complications.
Sensor technology for the rapid detection of the analytes with high sensitivity and selectivity has several challenges. Despite the challenges, colorimetric sensors have been widely accepted for its high sensitive and selective response towards various analytes. In this review, colorimetric sensors for the detection of biomolecules like protein, DNA, pathogen and chemical compounds like heavy metal ions, toxic gasses and organic compounds have been elaborately discussed. The visible sensing mechanism based on Surface Plasmon Resonance (SPR) using metal nanoparticles like Au, Ag, thin film interference using SiO2
and colorimetric array-based technique have been highlighted. The optical property of metal nanoparticles enables a visual color change during its interaction with the analytes owing to the dispersion and aggregation of nanoparticles. Recently, colorimetric changes using silica substrate for detection of protein and small molecules by thin film interference as a visible sensing mechanism has been developed without the usage of fluorescent or radioisotopes labels. Multilayer of biomaterials were used as a platform where reflection and interference of scattering light occur due to which color change happens leading to rapid sensing.
Colorimetric array-based technique for the detection of organic compounds using chemoresponsive dyes has also been focused wherein the interaction of the analytes with the substrate coated with chemoresponsive dyes gives colorimetric change.
In this work, a multimode optical fiber sensor probe coated with polypyrrole-polyethylene oxide (PPO) nanofibrous mat is investigated to detect volatile compounds such as ammonia, triethylamine, methanol, ethanol and acetone vapours. The fibrous mat on the fiber cladding is deposited using electrospinning method followed by vapour phase polymerization. The affinity of PPO towards different volatile compounds changes the effective refractive index of optical fiber cladding, modulating the intensity of the transmitted spectrum. The intensity variation in presence of volatile vapours of different concentration is investigated to determine the responses of the sensor probe. The sensor probe shows different detection limit such as 0.1 ppm, 2 ppm, 2 ppm, and 1 ppm and recovery time of 10 minutes, 54.4s, 21.06 s and 11.08 s for ammonia, ethanol, methanol and triethylamine vapours respectively. Thus, the electrospinning technique can be used for coating optical fiber cladding with special material such as PPO to develop optical fiber based sensor to detect trace amount of volatile compound.
As a futuristic diagnosis platform, breath analysis is gaining much attention because it is a noninvasive, simple, and low cost diagnostic method. Very promising clinical applications have been demonstrated for diagnostic purposes by correlation analysis between exhaled breath components and specific diseases. In addition, diverse breath molecules, which serve as biomarkers for specific diseases, are precisely identified by statistical pattern recognition studies. To further improve the accuracy of breath analysis as a diagnostic tool, breath sampling, biomarker sensing, and data analysis should be optimized. In particular, development of high performance breath sensors, which can detect biomarkers at the ppb-level in exhaled breath, is one of the most critical challenges. Due to the presence of numerous interfering gas species in exhaled breath, selective detection of specific biomarkers is also important.
Gas sensing properties of nanocrystalline bismuth oxide clad – modified fiber optic sensor is reported for ammonia, ethanol, methanol and acetone gasses at room temperature. The output of sensor increases or decreases for certain gasses when the concentration of the gas is increased. The sensor exhibits high response and good selectivity to methanol gas. Time response characteristics of the sensor are also reported.
Ultra-sensitive room-temperature operable gas sensors utilizing the photocatalytic activity of Na-doped p-type ZnO (Na:ZnO) nanoflowers (NFs) are demonstrated as a promising candidate for diabetes detection. The flowerlike Na:ZnO nano-particles possessing ultrathin hierarchical nanosheets were synthesized by a facile solution route at a low process temperature of 40 (o)C. It was found that the Na element acting as a p-type dopant was successfully incorporated in the ZnO lattice. Based on the synthesized p-type Na:ZnO NFs, room-temperature operable chemiresistive-type gas sensors were realized, activated by ultraviolet (UV) illumination. The Na:ZnO NF gas sensors exhibited high gas response (S of 3.35), fast response time (~18 sec) and recovery time (~63 sec) to acetone gas (100 ppm, UV intensity of 5 mW cm(-2)), and furthermore, sub-ppm level (0.2 ppm) detection was achieved at room-temperature, which enables the diagnosis of various diseases including the diabetes from exhaled breath.
Breath analysis not only holds great potential for the development of new non-invasive diagnostic methods, but also for the identification and follow up of drug levels in breath. This is of interest for both, forensic and medical science. On the one hand, the detection of drugs of abuse in exhaled breath - similar to the well-known breath alcohol tests - would be highly desirable as an alternative to blood or urine analysis in situations such as police controls for drugged driving. The noninvasive detection of drugs and their metabolites is thus of great interest in forensic science, especially since marijuana is becoming legalized in certain parts of the U.S. and the EU. The detection and monitoring of medical drugs in exhaled breath without the need of drawing blood samples on the other hand, is of high relevance in the clinical environment. This could facilitate a more precise medication and enable therapy control without any burden to the patient. Furthermore, it could be a step towards personalized medicine. This review gives an overview of the current state of drug detection in breath, including both volatile and non-volatile substances. The review is dividied into two sections. The first section deals with qualitative detection of drugs (drugs of abuse), while the second is related to quantitative drug detection (medical drugs). Chances and limitations are discussed for both aspects. The detection of the intravenous anesthetic propofol is presented as a detailed example that demonstrates the potential, requirements, pitfalls and limitations of therapeutic drug monitoring by means of breath analysis.
The increase of surface area and the functionalization of catalyst are crucial to develop high-performance semiconductor metal oxide (SMO) based chemi-resistive gas sensors. Herein, nanoscale catalyst loaded Co3O4 hollow nanocages (HNCs) by using metal-organic framework (MOF) templates have been developed as a new sensing platform. Nanoscale Pd nanoparticles (NPs) were easily loaded on the cavity of Co based zeolite imidazole framework (ZIF-67). The porous structure of ZIF-67 can restrict the size of Pd NPs (2–3 nm) and separate Pd NPs from each other. Subsequently, the calcination of Pd loaded ZIF-67 produced the catalytic PdO NPs functionalized Co3O4 HNCs (PdO-Co3O4 HNCs). The ultra-small PdO NPs (3–4 nm) are well-distributed in the wall of Co3O4 HNCs, the unique structure of which can provide high surface area and high catalytic activity. As a result, the PdO-Co3O4 HNCs exhibited improved acetone sensing response (Rgas/Rair = 2.51 to 5 ppm) compared to PdO-Co3O4 powders (Rgas/Rair = 1.98), Co3O4 HNCs (Rgas/Rair = 1.96), and Co3O4 powders (Rgas/Rair = 1.45). In addition, the PdO-Co3O4 HNCs showed high acetone selectivity against other interfering gases. Moreover, the sensor array clearly distinguished simulated exhaled breath of diabetics from healthy people’s breath. These results confirmed the novel synthesis of MOF templated nanoscale catalyst loaded SMO HNCs for high performance gas sensors.
Single-walled carbon nanotubes (SWNTs) have potential for creating high performance gas sensors, but the number of gases that can be detected is still limited and the sensitivity needs further improvement. Here, large-area SWNT films directly synthesized by chemical vapor deposition are configured into gas sensors for a range of toxic gases such as NH3, NO, and NO2. In particular, a SWNT-Fe2O3 composite film obtained via a simple annealing process produces a stable response to H2S and shows enhanced sensitivity to NO2 and at room temperature, compared with pristine SWNT films. Formation of uniform Fe2O3 nanoparticles throughout the porous film is responsible for improved performance and enabling sensing to more gases, and removes conventional steps such as chemical functionalization or doping. Flexible sensors that can be bent to large angles repeatedly are also demonstrated. SWNT films containing a large amount of residual catalyst can be directly manufactured into large-area, flexible or wearable, thin film or textile-configured sensors for various toxic gases.
This work presents a highly sensitive room-temperature gas sensor based on bilayer graphene fabricated by an interfacial transfer of chemical vapor deposited graphene onto nickel interdigitated electrodes. Scanning electron microscopic and Raman spectroscopic characterizations confirm the presence of graphene on interdigitated nickel electrodes with varying numbers of graphene layers. The NO2 detection performances of bilayer graphene gas sensor have been investigated in comparison with those of monolayer and multilayer graphene gas sensors at room temperature. From results, the bilayer graphene gas sensor exhibits higher response, sensitivity and selectivity to NO2 than monolayer and multilayer graphene. The sensitivity of bilayer graphene gas sensor is 1.409 ppm⁻¹ towards NO2 over a concentration range of 1–25 ppm, which is more than twice higher than that of monolayer graphene. The NO2-sensing mechanism of graphene sensing film has been explained based on the direct charge transfer process due to the adsorption of NO2 molecules.
The development of an evanescent wave optical fiber sensor modified with an organic–inorganic hybrid nanoporous thin film for the detection of organic solvent vapors was demonstrated. The optical fiber with a core diameter of 200 μm was bent into U-shape to enhance the penetration depth of light transferred into the evanescent field, and modified with a multilayered thin film of poly (allylamine hydrochloride) and silica nanoparticles (PAH/SiO2)n, via layer-by-layer (LbL) film deposition. The mesoporous film structure led to higher molecular diffusion and the highest selectivity to methanol among the six alcohols and water, which were used as target analytes, by the aid of tetrakis (4-sulfophenyl) porphine (TSPP) infused inside the film.
Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival. Incidence data were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data were collected by the National Center for Health Statistics. In 2017, 1,688,780 new cancer cases and 600,920 cancer deaths are projected to occur in the United States. For all sites combined, the cancer incidence rate is 20% higher in men than in women, while the cancer death rate is 40% higher. However, sex disparities vary by cancer type. For example, thyroid cancer incidence rates are 3-fold higher in women than in men (21 vs 7 per 100,000 population), despite equivalent death rates (0.5 per 100,000 population), largely reflecting sex differences in the "epidemic of diagnosis." Over the past decade of available data, the overall cancer incidence rate (2004-2013) was stable in women and declined by approximately 2% annually in men, while the cancer death rate (2005-2014) declined by about 1.5% annually in both men and women. From 1991 to 2014, the overall cancer death rate dropped 25%, translating to approximately 2,143,200 fewer cancer deaths than would have been expected if death rates had remained at their peak. Although the cancer death rate was 15% higher in blacks than in whites in 2014, increasing access to care as a result of the Patient Protection and Affordable Care Act may expedite the narrowing racial gap; from 2010 to 2015, the proportion of blacks who were uninsured halved, from 21% to 11%, as it did for Hispanics (31% to 16%). Gains in coverage for traditionally underserved Americans will facilitate the broader application of existing cancer control knowledge across every segment of the population. CA Cancer J Clin 2017. © 2017 American Cancer Society.
A highly sensitive ammonia (NH3) optical fiber sensor is demonstrated using platinum (Pt)-nanoparticle-incorporated graphene oxide (GO). The sensor was fabricated by coating a tapered microfiber multimode interferometer with Pt-decorated GO film. The sensing mechanism of the sensor was based on charge-transfer-induced refractive index changes in the GO: Pt nanoparticles which form an ideal assistant material can improve sensitivity remarkably for gas sensing. The experimental results show a sensitivity of 10.2 pm/ppm with Pt nanoparticles which is three times higher than the sensitivity when coated with pure GO. These results indicate the sensor has the optimal sensing sensitivity when the Pt nanoparticle concentration is 185.2 mg/L and exhibits a linear response with NH3 gas concentration below 80 ppm. This composite film-based passive optical fiber sensor provides an approach for highly sensitive NH3 sensing in a limited space and flammable or explosive environment.
Xylene is a hazardous volatile organic compound, which should be measured precisely for monitoring of indoor air quality. The selective detection of ppm-level xylene using oxide semiconductor chemiresistors, however, remains a challenging issue. In this study, NiO/NiMoO4 nanocomposite hierarchical spheres assembled from nanosheets were prepared by hydrothermal reaction, and the potential of sensors composed of these nanocomposites to selectively detect xylene gas was investigated. The sensors based on the NiO/NiMoO4 nanocomposite hierarchical spheres exhibited high responses (maximum resistance ratio = 101.5) to 5 ppm p-xylene with low cross-responses (resistance ratios < 30) to 5 ppm toluene, benzene, C2H5OH, CH3COCH3, HCHO, CO, trimethylamine, and NH3. In contrast, a sensor based on pure NiO hierarchical spheres exhibited negligibly low responses to all 9 analyte gases. The gas-sensing mechanism underlying the high selectivity and response to xylene in the NiO/NiMoO4 nanocomposite hierarchical spheres is discussed in relation to the catalytic promotion of the xylene-sensing reaction by synergistic combination between NiO and NiMoO4, gas-accessible hierarchical morphology, and electronic sensitization by Mo addition. Highly selective detection of xylene can pave the road toward a new solution for precise monitoring of indoor air pollution.
Ultra-selective and sensitive detection of carcinogenic benzene vapor with negligible interferences from other major indoor pollutants is not only critical but also challenging because the BTX gases (benzene, toluene, and xylene) are generally less reactive to a majority of n-type oxide semiconductor gas sensors and the similar chemical structures of BTX gases hamper their discrimination by chemiresistive variation. Through this paper, we propose a new strategy to detect sub-ppm-level benzene vapor in a highly selective manner using oxide semiconductor chemiresistors. A Pd-loaded SnO2 yolk-shell sensing film coated with a thin catalytic Co3O4 overlayer showed an ultrahigh response (resistance ratio = 88) to 5 ppm benzene with negligibly low cross-responses to the other representative and ubiquitous indoor pollutants such as toluene, xylene, HCHO, CO, and ethanol. The response to benzene vapor was significantly enhanced by reforming of highly stable benzene into more active and smaller species. The reforming was synergistically assisted by the Co3O4 catalytic overlayer and sensing layer consisting of Pd-loaded SnO2 micro-reactors, while the cross-responses to the other indoor pollutants became low because of the catalytic oxidation of the gases into less- or non-reactive species. This method will pave a new way to the precise monitoring of critically harmful benzene in both indoor and outdoor atmospheres.
Background:
Inflammatory bowel disease and irritable bowel syndrome may present in a similar manner. Measuring faecal calprotectin concentration is often recommended to rule out inflammatory bowel disease, however, there are no tests to positively diagnose irritable bowel syndrome and invasive tests are still used to rule out other pathologies.
Aim:
To investigate a platform technology for diagnosing inflammatory bowel disease and irritable bowel syndrome based on faecal gas.
Methods:
The platform technology is composed of a gas chromatography column coupled to a metal oxide gas sensor (OdoReader) and a computer algorithm. The OdoReader separates the volatile compounds from faecal gas and the computer algorithm identifies resistance patterns associated with specific medical conditions and builds classification models. This platform was applied to faecal samples from 152 patients: 33 patients with active inflammatory bowel disease; 50 patients with inactive inflammatory bowel disease; 28 patients with irritable bowel syndrome and 41 healthy donors (Control).
Results:
The platform classified samples with accuracies from 75% to 100% using rigorous validation schemes: namely leave-one-out cross-validation, 10-fold cross-validation, double cross-validation and their Monte Carlo variations. The most clinically important findings, after double cross-validation, were the accuracy of active Crohn's disease vs. irritable bowel syndrome (87%; CI 84-89%) and irritable bowel syndrome vs. controls (78%; CI 76-80%). These schemes provide an estimate of out-of-sample predictive accuracy for similar populations.
Conclusions:
This is the first description of an investigation for the positive diagnosis of irritable bowel syndrome, and for diagnosing inflammatory bowel disease.
Objectives:
Several studies associated altered gut microbiota composition in preterm infants with late-onset sepsis (LOS), up to days prior to clinical onset of sepsis. However, microbiota analysis as early diagnostic biomarker is in clinical practice currently not feasible because of logistic aspects and high costs. Therefore, we hypothesized that analysis of fecal volatile organic compounds (VOC) may serve as non-invasive biomarker to predict LOS at a preclinical stage, since VOC reflect the composition and activity of intestinal microbial communities.
Methods:
In a prospective multicenter study, fecal samples were collected daily from infants with a gestational age of <30 weeks. VOC signatures of fecal samples from infants with LOS, collected up to five days before diagnosis, were analyzed by means of an electronic nose technology (Cyranose 320®) and compared to matched controls.
Results:
Fecal VOC profiles of infants with LOS (n = 36) could be discriminated from controls (n = 40) at three days (AUC [± 95%CI], p-value, sensitivity, specificity; 70.2 [52.2-88.3], 0.033, 57.1%, 61.5%), two days (77.7 [62.7-92.7], 0.050, 75.0%, 70.8%) and one day (70.4 [49.6-91.3], 0.037, 64.3%, 64.3%) before the onset of LOS.
Conclusions:
Fecal VOC profiles of preterm infants with LOS could be discriminated from matched controls, up to three days before clinical onset of the disease, underlining the hypothesis that intestinal microbiota may play an etiological role in LOS. Notably, VOC profiling is clinically feasible and the potential of this technique in the early detection of LOS needs to be confirmed in future studies.
In this work, a novel catalytic synthesis and functionalization method using apoferritin is used to fabricate RuO2 nanoparticles (NPs) loaded WO3 nanofibers (NFs) for potential diagnosis of diabetes. Catalytic ruthenium (Ru) NPs with very small average diameters of 1.8 ± 0.9 nm were synthesized using apoferritin which is a hollow protein cage, and were easily functionalized on WO3 NFs by introducing electrospinning solution with W precursor and polyvinylpyrrolidone (PVP). As-spun Ru NPs-loaded W precursor/PVP composite NFs were calcined at 600 °C for 1 h in air atmosphere to achieve RuO2-functionalized WO3 NFs. The small size and uniform distribution of catalytic RuO2 NPs were well maintained due to hollow nature of apoferritin cages after calcination. The chemo-resistive sensors using RuO2-functionalized WO3 NFs showed significantly enhanced acetone (CH3COCH3) sensing response (Rair/Rgas = 78.61 to 5 ppm), which was 7.4 times higher than the response (Rair/Rgas = 10.61 to 5 ppm) of pristine WO3 NFs at highly humid atmosphere (95% RH). In addition, the RuO2-functionalized WO3 NFs showed outstanding selectivity toward acetone gas in comparison with other gases such as hydrogen sulfide (H2S), toluene (C6H5CH3), ethanol (C2H5OH), pentane (C5H12), ammonia (NH3), hydrogen (H2), and water vapor (H2O) at 5 ppm. These results represent potential feasibility for the detection of acetone in exhaled breath for diagnosis of diabetes.
Carbon nanotube based gas sensors can be used to detect harmful environmental pollutants such as NO2 at room temperature. Whilst showing promise as low powered, sensitive and affordable monitoring devices, cross-sensitivity of functionalised carbon nanotubes to water vapour often obscures the detection of target molecules. This is a barrier to adoption for monitoring of airborne pollutants due to the varying humidity levels found in real world environments. Zeolites, also known as molecular sieves due to their selective adsorption properties, are used in this work to control the cross-sensitivity of single-walled carbon nanotube (SWCNT) based sensors to water vapour. Zeolites incorporated into the sensing layer are found to reduce interference effects that would otherwise obscure the identification of NO2 gas, permitting repeatable detection over a range of relative humidities. This significant improvement is found to depend on the arrangement of the SWCNT-zeolite layers in the sensing device, as well as the hydrophilicity of the chosen zeolite.