Detection of nonpolar molecules by means of carrier scattering in random networks of carbon nanotubes: toward diagnosis of diseases via breath samples

1D and 2D Field Effect Transistors in Gas Sensing: A Comprehensive Review

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.

Artificially Intelligent Nanoarray Detects Various Cancers by Liquid Biopsy of Volatile Markers

Cancer is usually not symptomatic in its early stages. However, early detection can vastly improve prognosis. Liquid biopsy holds great promise for early detection, although it still suffers from many disadvantages, mainly searching for specific cancer biomarkers. Here, a new approach for liquid biopsies is proposed, based on volatile organic compound (VOC) patterns in the blood headspace. An artificial intelligence nanoarray based on a varied set of chemi-sensitive nano-based structured films is developed and used to detect and stage cancer. As a proof-of-concept, three cancer models are tested showing high incidence and mortality rates in the population: breast cancer, ovarian cancer, and pancreatic cancer. The nanoarray has >84% accuracy, >81% sensitivity, and >80% specificity for early detection and >97% accuracy, 100% sensitivity, and >88% specificity for metastasis detection. Complementary mass spectrometry analysis validates these results. The ability to analyze such a complex biological fluid as blood, while considering data of many VOCs at a time using the artificially intelligent nanoarray, increases the sensitivity of predictive models and leads to a potential efficient early diagnosis and disease-monitoring tool for cancer.

Breath Analysis: A Promising Tool for Disease Diagnosis-The Role of Sensors

Early-stage disease diagnosis is of particular importance for effective patient identification as well as their treatment. Lack of patient compliance for the existing diagnostic methods, however, limits prompt diagnosis, rendering the development of non-invasive diagnostic tools mandatory. One of the most promising non-invasive diagnostic methods that has also attracted great research interest during the last years is breath analysis; the method detects gas-analytes such as exhaled volatile organic compounds (VOCs) and inorganic gases that are considered to be important biomarkers for various disease-types. The diagnostic ability of gas-pattern detection using analytical techniques and especially sensors has been widely discussed in the literature; however, the incorporation of novel nanomaterials in sensor-development has also proved to enhance sensor performance, for both selective and cross-reactive applications. The aim of the first part of this review is to provide an up-to-date overview of the main categories of sensors studied for disease diagnosis applications via the detection of exhaled gas-analytes and to highlight the role of nanomaterials. The second and most novel part of this review concentrates on the remarkable applicability of breath analysis in differential diagnosis, phenotyping, and the staging of several disease-types, which are currently amongst the most pressing challenges in the field.

Models for sensing by nanowire networks: application to organic vapour detection by multiwall carbon nanotube-DNA films

Electronic sensors for volatile organic compounds have been prepared by drop-casting dispersions of multi-wall carbon nanotubes (MWCNTs) in aqueous solutions ofλ-DNA onto Pt microband electrodes. The MWCNTs themselves show a metal-like temperature dependence of the conductance, but the conductance of DNA/MWCNT composites has an activated component that corresponds to inter-tube tunneling. The resistance of the composite was modelled by a series combination of a term linear in temperature for the nanotubes and a stretched exponential form for the inter-tube junctions. The resistance may increase or decrease with temperature according to the composition and may be tuned to be almost temperature-independent at 67% by mass of DNA. Upon exposure to organic vapours, the resistance of the composites increases and the time-dependence of this signal is consistent with diffusion of the vapour into the composite. The fractional change in resistance at steady-state provides an analytical signal with a linear calibration and the presence of DNA enhances the signal and adjusts the selectivity in favour of polar analytes. The temperature dependence of the signal is determined by the enthalpy of adsorption of the analyte in the inter-tube junctions and may be satisfactorily modelled using the Langmuir isotherm. Temperature and pressure-dependent studies indicate that neither charge injection by oxidation/reduction of the analyte nor condensation of analyte on the device is responsible for the signal. We suggest that the origin of the sensing response is an adsorption of the analyte in the inter-tube regions that modulates the tunneling barriers. This suggests a general route to tuning the selectivity of MWCNT gas sensors using non-conductive polymers of varying chemical functionality.

Breath volatile organic compound analysis: an emerging method for gastric cancer detection

Gastric cancer is a common malignancy, being the fifth most frequently diagnosed cancer and the fourth leading cause of cancer-related deaths worldwide. Diagnosis of gastric cancer at the early stage is critical to effectively improve the survival rate. However, a substantial proportion of patients with gastric cancer in the early stages lack specific symptoms or are asymptomatic. Moreover, the imaging techniques currently used for gastric cancer screening, such as computed tomography and barium examination, are usually radioactive and have low sensitivity and specificity. Even though endoscopy has high accuracy for gastric cancer screening, its application is limited by the invasiveness of the technique. Breath analysis is an economic, effective, easy to perform, non-invasive detection method, and has no undesirable side effects on subjects. Extensive worldwide research has been conducted on breath volatile organic compounds (VOCs), which reveals its prospect as a potential method for gastric cancer detection. Many interesting results have been obtained and innovative methods have been introduced in this subject; hence, an extensive review would be beneficial. By providing a comprehensive list of breath VOCs identified by gastric cancer would promote further research in this field. This review summarizes the commonly used technologies for exhaled breath analysis, focusing on the application of analytical instruments in the detection of breath VOCs in gastric cancers, and the alterations in the profile of breath biomarkers in gastric cancer patients are discussed as well.

Detection of Single Cancer Cells in Blood with Artificially Intelligent Nanoarray

Detection and monitoring of single cancer cells (SCCs), such as circulating tumor cells (CTCs), would be of aid in an efficient early detection of cancer, a tailored (personalized) therapy, and in a fast bedside assessment of treatment efficacy. Nevertheless, currently available techniques, which mostly rely on the isolation of SCCs based on their physical or biological properties, suffer from low sensitivity, complicated technical procedures, low cost-effectiveness, and being unsuitable for continuous monitoring. We report here on the design and use of an artificially intelligent nanoarray based on a heterogeneous set of chemisensitive nanostructured films for the detection of SCCs using volatile organic compounds emanating in the air trapped above blood samples containing SCCs. For demonstration purposes, we have focused on samples containing A549 lung cancer cells (hereafter, SCC^A549). The nanoarray developed to detect SCC^A549 has >90% accuracy, >85% sensitivity, and >95% specificity. Detection works irrespective of the medium and/or the environment. These results were validated by complementary mass spectrometry. The ability to continuously record, store, and preprocess the signals increases the chances that this nanotechnology might also be useful in the early detection of cancer cells in the blood and continuous monitoring of their possible progression.

Rational Design of Semiconductor-Based Chemiresistors and their Libraries for Next-Generation Artificial Olfaction

Artificial olfaction based on gas sensor arrays aims to substitute for, support, and surpass human olfaction. Like mammalian olfaction, a larger number of sensors and more signal processing are crucial for strengthening artificial olfaction. Due to rapid progress in computing capabilities and machine-learning algorithms, on-demand high-performance artificial olfaction that can eclipse human olfaction becomes inevitable once diverse and versatile gas sensing materials are provided. Here, rational strategies to design a myriad of different semiconductor-based chemiresistors and to grow gas sensing libraries enough to identify a wide range of odors and gases are reviewed, discussed, and suggested. Key approaches include the use of p-type oxide semiconductors, multinary perovskite and spinel oxides, carbon-based materials, metal chalcogenides, their heterostructures, as well as heterocomposites as distinctive sensing materials, the utilization of bilayer sensor design, the design of robust sensing materials, and the high-throughput screening of sensing materials. In addition, the state-of-the-art and key issues in the implementation of electronic noses are discussed. Finally, a perspective on chemiresistive sensing materials for next-generation artificial olfaction is provided.

Chemiresistive Sensor Array and Machine Learning Classification of Food

Successful identification of complex odors by sensor arrays remains a challenging problem. Herein, we report robust, category-specific multiclass-time series classification using an array of 20 carbon nanotube-based chemical sensors. We differentiate between samples of cheese, liquor, and edible oil based on their odor. In a two-stage machine-learning approach, we first obtain an optimal subset of sensors specific to each category and then validate this subset using an independent and expanded data set. We determined the optimal selectors via independent selector classification accuracy, as well as a combinatorial scan of all 4845 possible four selector combinations. We performed sample classification using two models-a k-nearest neighbors model and a random forest model trained on extracted features. This protocol led to high classification accuracy in the independent test sets for five cheese and five liquor samples (accuracies of 91% and 78%, respectively) and only a slightly lower (73%) accuracy on a five edible oil data set.

Carbon Nanotube Chemical Sensors

Carbon nanotubes (CNTs) promise to advance a number of real-world technologies. Of these applications, they are particularly attractive for uses in chemical sensors for environmental and health monitoring. However, chemical sensors based on CNTs are often lacking in selectivity, and the elucidation of their sensing mechanisms remains challenging. This review is a comprehensive description of the parameters that give rise to the sensing capabilities of CNT-based sensors and the application of CNT-based devices in chemical sensing. This review begins with the discussion of the sensing mechanisms in CNT-based devices, the chemical methods of CNT functionalization, architectures of sensors, performance parameters, and theoretical models used to describe CNT sensors. It then discusses the expansive applications of CNT-based sensors to multiple areas including environmental monitoring, food and agriculture applications, biological sensors, and national security. The discussion of each analyte focuses on the strategies used to impart selectivity and the molecular interactions between the selector and the analyte. Finally, the review concludes with a brief outlook over future developments in the field of chemical sensors and their prospects for commercialization.

Influence of Water Molecules on the Detection of Volatile Organic Compounds (VOC) Cancer Biomarkers by Nanocomposite Quantum Resistive Vapor Sensors vQRS

The anticipated diagnosis of various fatal diseases from the analysis of volatile organic compounds (VOC) biomarkers of the volatolome is the object of very dynamic research. Nanocomposite-based quantum resistive vapor sensors (vQRS) exhibit strong advantages in the detection of biomarkers, as they can operate at room temperature with low consumption and sub ppm (part per million) sensitivity. However, to meet this application they need to detect some ppm or less amounts of biomarkers in patients' breath, skin, or urine in complex blends of numerous VOC, most of the time hindered by a huge amount of water molecules. Therefore, it is crucial to analyze the effects of moisture on the chemo-resistive sensing behavior of carbon nanotubes based vQRS. We show that in the presence of water molecules, the sensors cannot detect the right amount of VOC molecules present in their environment. These perturbations of the detection mechanism are found to depend on the chemical interactions between water and other VOC molecules, but also on their competitive absorption on sensors receptive sites, located at the nanojunctions of the conductive architecture. This complex phenomenon studied with down to 12.5 ppm of acetone, ethanol, butanone, toluene, and cyclohexane mixed with 100 ppm of water was worth to investigate in the prospect of future developments of devices analysing real breath samples in which water can reach a concentration of 6%.

Ionic Liquid-Carbon Nanotube Sensor Arrays for Human Breath Related Volatile Organic Compounds

High sensitivity, selectivity, and stability are key requirements for carbon nanotube (CNT)-based sensors to realize their full potential in applications ranging from chemical warfare agent detection to disease diagnostics. Herein we demonstrate the sensing of volatile organic compounds (VOCs) relevant to human diseases using an array of chemiresistive carbon nanotube (CNT)-based sensors functionalized with ionic liquids (ILs). The ILs are fluid at ambient temperature and were selected to produce a discriminating sensor array capable of the gas-phase detection of human disease-related VOCs. We find that sensor arrays consisting of imidazolium-based ILs with different substituents and counterions provide selective responses for known biomarkers of infectious diseases of the lungs. Specifically, the sensors discriminate the various volatile biomarkers for tuberculosis based on their polarity, solubility, and chemical affinities. In addition to selectivity, the sensors also show a high level of reversibility and promising long-term stability, which renders them to be suitable candidates for practical applications in breath analysis.

Sensor Array for Detection of Early Stage Parkinson's Disease before Medication

Early diagnosis of Parkinson's disease (PD) is important because it affects the choice of therapy and is subject to a relatively high degree of error. In addition, early detection of PD can potentially enable the start of neuroprotective therapy before extensive loss of dopaminergic neurons of the substantia nigra occurs. However, until now, studies for early detection of PD using volatile biomarkers sampled only treated and medicated patients. Therefore, there is a great need to evaluate untreated patients for establishing a real world screening and diagnostic technology. Here we describe for the first time a clinical trial to distinguish between de novo PD and control subjects using an electronic system for detection of volatile molecules in exhaled breath (sensor array). We further determine for the first time the association to other common tests for PD diagnostics as smell, ultrasound, and nonmotor symptoms. The test group consisted of 29 PD patients after initial diagnosis by an experienced neurologist, compared with 19 control subjects of similar age. The sensitivity, specificity, and accuracy values of the sensor array to detect PD from controls were 79%, 84%, and 81% respectively, in comparison with midbrain ultrasonography (93%, 90%, 92%) and smell detection (62%, 89%, 73%). The results confirm previous data showing the potential of sensor arrays to detect PD.

Synergy between nanomaterials and volatile organic compounds for non-invasive medical evaluation

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.

Altered Volatile Organic Compound Profile in Transgenic Rats Bearing A53T Mutation of Human α-Synuclein: Comparison with Dopaminergic and Serotonergic Denervation

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 (α-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.

The Role of Nanomechanics in Healthcare

Nanomechanics has played a vital role in pushing our capability to detect, probe, and manipulate the biological species, such as proteins, cells, and tissues, paving way to a deeper knowledge and superior strategies for healthcare. Nanomechanical characterization techniques, such as atomic force microscopy, nanoindentation, nanotribology, optical tweezers, and other hybrid techniques have been utilized to understand the mechanics and kinetics of biospecies. Investigation of the mechanics of cells and tissues has provided critical information about mechanical characteristics of host body environments. This information has been utilized for developing biomimetic materials and structures for tissue engineering and artificial implants. This review summarizes nanomechanical characterization techniques and their potential applications in healthcare research. The principles and examples of label-free detection of cancers and myocardial infarction by nanomechanical cantilevers are discussed. The vital importance of nanomechanics in regenerative medicine is highlighted from the perspective of material selection and design for developing biocompatible scaffolds. This review interconnects the advancements made in fundamental materials science research and biomedical technology, and therefore provides scientific insight that is of common interest to the researchers working in different disciplines of healthcare science and technology.

Sulfonated poly(ether ether ketone) [SPEEK] nanocomposites based on hybrid nanocarbons for the detection and discrimination of some lung cancer VOC biomarkers

The analysis of a volatolome is a promising approach to allow the early diagnosis of diseases such as cancers. However, one important challenge is to take the chemical fingerprint of the complex blend of volatiles, for many of them only present at the sub-ppm level. We have investigated a facile route to differentiate the chemo-resistive behaviour of quantum resistive vapour sensors (vQRS) and provide them with a strong methanol selectivity by simply changing the sulfonation degree of poly(ether ether ketone) up to 85%. The hybridization of carbon nanotubes (CNTs) with fullerene (C₆₀) structured in a 3D architecture by spray layer-by-layer (sLbL) has allowed us to boost significantly the sensitivity of sensors to reach the sub-ppm level (340 ppb). After their integration into an e-nose, PEEK-nanocarbon sensors were found to effectively discriminate both single and binary mixtures of volatile organic compounds (VOCs) and among all biomarkers to detect preferentially methanol with a high signal to noise ratio (200).

Differentiation between genetic mutations of breast cancer by breath volatolomics

Mapping molecular sub-types in breast cancer (BC) tumours is a rapidly evolving area due to growing interest in, for example, targeted therapy and screening high-risk populations for early diagnosis. We report a new concept for profiling BC molecular sub-types based on volatile organic compounds (VOCs). For this purpose, breath samples were collected from 276 female volunteers, including healthy, benign conditions, ductal carcinoma in situ (DCIS) and malignant lesions. Breath samples were analysed by gas chromatography mass spectrometry (GC-MS) and artificially intelligent nanoarray technology. Applying the non-parametric Wilcoxon/Kruskal-Wallis test, GC-MS analysis found 23 compounds that were significantly different (p < 0.05) in breath samples of BC patients with different molecular sub-types. Discriminant function analysis (DFA) of the nanoarray identified unique volatolomic signatures between cancer and non-cancer cases (83% accuracy in blind testing), and for the different molecular sub-types with accuracies ranging from 82 to 87%, sensitivities of 81 to 88% and specificities of 76 to 96% in leave-one-out cross-validation. These results demonstrate the presence of detectable breath VOC patterns for accurately profiling molecular sub-types in BC, either through specific compound identification by GC-MS or by volatolomic signatures obtained through statistical analysis of the artificially intelligent nanoarray responses.

Electrical gas sensors based on structured organic ultra-thin films and nanocrystals on solid state substrates

Gas sensors, as useful tools to detect specific gas species such as toxic and explosive gases or volatile organic compounds, are the key components for environmental monitoring, fruit maturity and food safety monitoring, health care, and so on. The present commercial products based on porous metal oxide materials still face problems, such as high temperature operation and low level of selectivity. Thin films or nanostructures of organic materials with thickness or grain size down to nanometer scale represent promising candidates for gas sensing due to their potential for achieving high selectivity, portability and low cost. However, there are still challenges related to their stability, reproducibility and response/recovery speed despite the efforts in materials design, morphology control or device configuration, all of which have been expended during the last few decades. In this review, we summarize the progress of recent research on gas sensors based on organic ultra-thin films and nanostructures. We specifically discuss the effect of microstructure in the active layer on the sensing performance and mechanism.

Detection of volatile organic compounds (VOCs) from exhaled breath as noninvasive methods for cancer diagnosis

The detection of cancer at an early stage is often significant in the successful treatment of the disease. Tumor cells have been reported to generate unique cancer volatile organic compound (VOC) profiles which can reflect the disease conditions. The detection and analysis of VOC biomarkers from exhaled breath has been recognized as a new frontier in cancer diagnostics and health inspections owing to its potential in developing rapid, noninvasive, and inexpensive cancer screening tools. To detect specific VOCs of low concentrations from exhaled breath, and to enhance the accuracy of early diagnosis, many breath collection and analysis approaches have been developed. This paper will summarize and critically review the exhaled-breath VOC-related sampling, collection, detection, and analytical methods, especially the recent development in VOC sensors. VOC sensors are commonly inexpensive, portable, programmable, easy to use, and can obtain data in real time with high sensitivities. Therefore, many sensor-based VOC detection techniques have huge potential in clinical point-of-care use.

Study on adsorption and desorption of ammonia on graphene

The gas sensor based on pristine graphene with conductance type was studied theoretically and experimentally. The time response of conductance measurements showed a quickly and largely increased conductivity when the sensor was exposed to ammonia gas produced by a bubble system of ammonia water. However, the desorption process in vacuum took more than 1 h which indicated that there was a larger number of transferred carriers and a strong adsorption force between ammonia and graphene. The desorption time could be greatly shortened down to about 2 min by adding the flow of water-vapor-enriched air at the beginning of the recovery stage which had been confirmed as a rapid and high-efficiency desorption process. Moreover, the optimum geometries, adsorption energies, and the charge transfer number of the composite systems were studied with first-principle calculations. However, the theoretical results showed that the adsorption energy between NH3 and graphene was too small to fit for the experimental phenomenon, and there were few charges transferred between graphene and NH3 molecules, which was completely different from the experiment measurement. The adsorption energy between NH4 and graphene increased stage by stage which showed NH4 was a strong donor. The calculation suggested that H2O molecule could help a quick desorption of NH4 from graphene by converting NH4 to NH3 or (NH3)n(H2O)m groups, which was consistent with the experimental results. This study demonstrates that the ammonia gas produced by a bubble system of ammonia water is mainly ammonium groups of NH3 and NH4, and the NH4 moleculars are ideal candidates for the molecular doping of graphene while the interaction between graphene and the NH3 moleculars is weak.

Nanoscale Sensor Technologies for Disease Detection via Volatolomics

The detection of many diseases is missed because of delayed diagnoses or the low efficacy of some treatments. This emphasizes the urgent need for inexpensive and minimally invasive technologies that would allow efficient early detection, stratifying the population for personalized therapy, and improving the efficacy of rapid bed-side assessment of treatment. An emerging approach that has a high potential to fulfill these needs is based on so-called "volatolomics", namely, chemical processes involving profiles of highly volatile organic compounds (VOCs) emitted from body fluids, including breath, skin, urine and blood. This article presents a didactic review of some of the main advances related to the use of nanomaterial-based solid-state and flexible sensors, and related artificially intelligent sensing arrays for the detection and monitoring of disease with volatolomics. The article attempts to review the technological gaps and confounding factors related to VOC testing. Different ways to choose nanomaterial-based sensors are discussed, while considering the profiles of targeted volatile markers and possible limitations of applying the sensing approach. Perspectives for taking volatolomics to a new level in the field of diagnostics are highlighted.

Measuring Compounds in Exhaled Air to Detect Alzheimer's Disease and Parkinson's Disease

Background

Alzheimer’s disease (AD) is diagnosed based upon medical history, neuropsychiatric examination, cerebrospinal fluid analysis, extensive laboratory analyses and cerebral imaging. Diagnosis is time consuming and labour intensive. Parkinson’s disease (PD) is mainly diagnosed on clinical grounds.

Objective

The primary aim of this study was to differentiate patients suffering from AD, PD and healthy controls by investigating exhaled air with the electronic nose technique. After demonstrating a difference between the three groups the secondary aim was the identification of specific substances responsible for the difference(s) using ion mobility spectroscopy. Thirdly we analysed whether amyloid beta (Aβ) in exhaled breath was causative for the observed differences between patients suffering from AD and healthy controls.

Methods

We employed novel pulmonary diagnostic tools (electronic nose device/ion-mobility spectrometry) for the identification of patients with neurodegenerative diseases. Specifically, we analysed breath pattern differences in exhaled air of patients with AD, those with PD and healthy controls using the electronic nose device (eNose). Using ion mobility spectrometry (IMS), we identified the compounds responsible for the observed differences in breath patterns. We applied ELISA technique to measure Aβ in exhaled breath condensates.

Results

The eNose was able to differentiate between AD, PD and HC correctly. Using IMS, we identified markers that could be used to differentiate healthy controls from patients with AD and PD with an accuracy of 94%. In addition, patients suffering from PD were identified with sensitivity and specificity of 100%. Altogether, 3 AD patients out of 53 participants were misclassified. Although we found Aβ in exhaled breath condensate from both AD and healthy controls, no significant differences between groups were detected.

Conclusion

These data may open a new field in the diagnosis of neurodegenerative disease such as Alzheimer’s disease and Parkinson’s disease. Further research is required to evaluate the significance of these pulmonary findings with respect to the pathophysiology of neurodegenerative disorders.

Monolayer-capped gold nanoparticles for disease detection from breath

The recognition of volatile organic compounds in breath samples is a promising approach for noninvasive safe diagnosis of disease. Spectrometry and spectroscopy methods used for breath analysis suffer from suboptimal accuracy, are expensive and are unsuitable for diagnostics. This article presents a concise review on arrays of monolayer-capped gold nanoparticle (GNP) sensors in conjugation with pattern recognition methods for cost-effective, fast and high-throughput point-of-care diagnostic results from exhaled breath samples. The article starts with a general introduction to the rationale and advantages of breath analysis as well as with a presentation of the utility of monolayer-capped GNP sensors in this field. The article continues with a presentation of the main fabrication and operation principles of these GNP sensors and concludes with selected examples regarding their utility in different fields of medicine, particularly in neurology, infectiology, respiratory medicine and oncology.

Synthesis, Structure, and Ethanol Gas Sensing Properties of In2O3 Nanorods Decorated with Bi2O3 Nanoparticles

Bi2O3-decorated In2O3 nanorods were synthesized using a one-step process, and their structure, as well as the effects of decoration of In2O3 nanorods with Bi2O3 on the ethanol gas-sensing properties were examined. The multiple networked Bi2O3-decorated In2O3 nanorod sensor showed responses of 171-1774% at ethanol concentrations of 10-200 ppm at 200 °C. The responses of the Bi2O3-decorated In2O3 nanorod sensor were stronger than those of the pristine-In2O3 nanorod sensors by 1.5-4.9 times at the corresponding concentrations. The two sensors exhibited short response times and long recovery times. The optimal Bi concentration in the Bi2O3-decorated In2O3 nanorod sensor and the optimal operation temperature of the sensor were 20% and 200 °C, respectively. The Bi2O3-decorated In2O3 nanorod sensor showed selectivity for ethanol gas over other gases. The origin of the enhanced response, sensing speed, and selectivity for ethanol gas of the Bi2O3-decorated In2O3 nanorod sensor to ethanol gas is discussed.

Comprehensive spectroscopic studies on the interaction of biomolecules with surfactant detached multi-walled carbon nanotubes

This paper investigates the interaction of ten diverse biomolecules with surfactant detached Multi-Walled Carbon Nanotubes (MWCNTs) using multiple spectroscopic methods. Declining fluorescence intensity of biomolecules in combination with the hyperchromic effect in UV-Visible spectra confirmed the existence of the ground state complex formation. Quenching mechanism remains static and non-fluorescent. 3D spectral data of biomolecules suggested the possibilities of disturbances to the aromatic microenvironment of tryptophan and tyrosine residues arising out of CNTs interaction. Amide band Shifts corresponding to the secondary structure of biomolecules were observed in the of FTIR and FT-Raman spectra. In addition, there exists an increased Raman intensity of tryptophan residues of biomolecules upon interaction with CNTs. Hence, the binding of the aromatic structures of CNTs with the aromatic amino acid residues, in a particular, tryptophan was evidenced. Far UV Circular spectra have showed the loss of alpha-helical contents in biomolecules upon interaction with CNTs. Near UV CD spectra confirmed the alterations in the tryptophan positions of the peptide backbone. Hence, our results have demonstrated that the interaction of biomolecules with OH-MWCNTs would involve binding cum structural changes and alteration to their aromatic micro-environment.

Ultrasensitive QRS made by supramolecular assembly of functionalized cyclodextrins and graphene for the detection of lung cancer VOC biomarkers

A novel electronic nose system comprising functionalized β-cyclodextrin wrapped reduced graphene oxide (RGO) sensors with distinct ability of discrimination of a set of volatile organic compounds has been developed. Non-covalent modification of chemically functionalized cyclodextrin with RGO is carried out by using pyrene adamantane as a linker wherever necessary, in order to construct a supramolecular assembly. The chemical functionality on cyclodextrin is varied utilising the principle of selective chemical modification of cyclodextrin. In the present study, the combined benefits of the host-guest inclusion complex formation ability and tunable chemical functionality of cyclodextrin, as well as the high surface area and electrical conductivity of graphene, are utilized for the development of a set of highly selective quantum resistive chemical vapour sensors (QRS), which can be assembled in an electronic nose.

Artificial sensing intelligence with silicon nanowires for ultraselective detection in the gas phase

The use of molecularly modified Si nanowire field effect transistors (SiNW FETs) for selective detection in the liquid phase has been successfully demonstrated. In contrast, selective detection of chemical species in the gas phase has been rather limited. In this paper, we show that the application of artificial intelligence on deliberately controlled SiNW FET device parameters can provide high selectivity toward specific volatile organic compounds (VOCs). The obtained selectivity allows identifying VOCs in both single-component and multicomponent environments as well as estimating the constituent VOC concentrations. The effect of the structural properties (functional group and/or chain length) of the molecular modifications on the accuracy of VOC detection is presented and discussed. The reported results have the potential to serve as a launching pad for the use of SiNW FET sensors in real-world counteracting conditions and/or applications.

Assessment, origin, and implementation of breath volatile cancer markers

A new non-invasive and potentially inexpensive frontier in the diagnosis of cancer relies on the detection of volatile organic compounds (VOCs) in exhaled breath samples. Breath can be sampled and analyzed in real-time, leading to fascinating and cost-effective clinical diagnostic procedures. Nevertheless, breath analysis is a very young field of research and faces challenges, mainly because the biochemical mechanisms behind the cancer-related VOCs are largely unknown. In this review, we present a list of 115 validated cancer-related VOCs published in the literature during the past decade, and classify them with respect to their "fat-to-blood" and "blood-to-air" partition coefficients. These partition coefficients provide an estimation of the relative concentrations of VOCs in alveolar breath, in blood and in the fat compartments of the human body. Additionally, we try to clarify controversial issues concerning possible experimental malpractice in the field, and propose ways to translate the basic science results as well as the mechanistic understanding to tools (sensors) that could serve as point-of-care diagnostics of cancer. We end this review with a conclusion and a future perspective.

Volatile organic compounds and the potential for a lung cancer breath test

SUMMARY Detecting exhaled volatile organic compounds (VOCs) that are associated with lung cancer (LC) has realistic potential for becoming an integral part of population-based LC screening and monitoring in the near future. Here, we review the main three approaches for profiling VOCs in LC patients and their advantages and pitfalls: first, mass spectrometry techniques for the identification and/or quantification of a wide variety of separate breath VOCs; second, canines that are trained to sniff out LC; and third, cross-reactive chemical sensors in combination with statistical methods for identifying disease-specific patterns. We estimate that the latter would be most suitable for clinical practice. In the short run, breath testing could provide a critically needed adjunct method for detecting nodule malignancy with high specificity during low-dose computed tomography screening. In the long run, breath testing holds potential for entirely revolutionizing LC screening, diagnosis and management.

Nanomaterial-based sensors for detection of disease by volatile organic compounds

The importance of developing new diagnostic and detection technologies for the growing number of clinical challenges is rising each year. Here, we present a concise, yet didactic review on a new diagnostics frontier based on the detection of disease-related volatile organic compounds (VOCs) by means of nanomaterial-based sensors. Nanomaterials are ideal for such sensor arrays because they are easily fabricated, chemically versatile and can be integrated into currently available sensing platforms. Following a general introduction, we provide a brief description of the VOC-related diseases concept. Then, we focus on detection of VOC-related diseases by selective and crossreactive sensing approaches, through chemical, optical and mechanical transducers incorporating the most important classes of nanomaterials. Selected examples of the integration of nanomaterials into selective sensors and crossreactive sensor arrays are given. We conclude with a brief discussion on the integration possibilities of different types of nanomaterials into sensor arrays, and the expected outcomes and limitations.

Rapid prototyping of carbon-based chemiresistive gas sensors on paper

Chemically functionalized carbon nanotubes (CNTs) are promising materials for sensing of gases and volatile organic compounds. However, the poor solubility of carbon nanotubes hinders their chemical functionalization and the subsequent integration of these materials into devices. This manuscript describes a solvent-free procedure for rapid prototyping of selective chemiresistors from CNTs and graphite on the surface of paper. This procedure enables fabrication of functional gas sensors from commercially available starting materials in less than 15 min. The first step of this procedure involves the generation of solid composites of CNTs or graphite with small molecule selectors--designed to interact with specific classes of gaseous analytes--by solvent-free mechanical mixing in a ball mill and subsequent compression. The second step involves deposition of chemiresistive sensors by mechanical abrasion of these solid composites onto the surface of paper. Parallel fabrication of multiple chemiresistors from diverse composites rapidly generates cross-reactive arrays capable of sensing and differentiating gases and volatile organic compounds at part-per-million and part-per-thousand concentrations.

Effect of chain length on the sensing of volatile organic compounds by means of silicon nanowires

Molecularly modified silicon nanowire field effect transistors (SiNW FETs) are starting to appear as promising devices for sensing various volatile organic compounds (VOCs). Understanding the connection between the molecular layer structure attached to the SiNWs and VOCs is essential for the design of high performance sensors. Here, we explore the chain length influence of molecular layers on the sensing performance to polar and nonpolar VOCs. SiNW FETs were functionalized with molecular layers that have similar end (methyl) group and amide bridge bond, but differ in their alkyl chain lengths. The resulting devices were then exposed to polar and nonpolar VOCs in various concentrations. Our results showed that the sensing response to changing the threshold voltage (ΔVth) and changing the relative hole mobility (Δμh/μh-a) have a proportional relationship to the VOC concentration. On exposure to a specific VOC concentration, ΔVth response increased with the chain length of the molecular modification. In contrast, Δμh/μh-a did not exhibit any obvious reliance on the chain length of the molecular layer. Analysis of the responses with an electrostatic-based model suggests that the sensor response in ΔVth is dependent on the VOC concentration, VOC vapor pressure, VOC-molecular layer binding energy, and VOC adsorption-induced dipole moment changes of molecular layer.

Interaction of carboxylated single-walled carbon nanotubes with bovine serum albumin

Carboxylated single-walled carbon nanotubes (c-SWNTs) were synthesized prosperously in order to improve dispersion of raw carbon nanotubes. Then, bovine serum albumin (BSA) was used as the template protein to study the biocompatibility of c-SWNTs by UV-Vis, fluorescence and circular dichroism (CD) spectroscopic methods at the molecular level. Results from fluorescence spectrum showed obvious decreases in fluorescence intensity of BSA induced by c-SWNTs, indicating the occurrence of interaction between BSA and c-SWNTs. Static quenching effect of c-SWNTs was verified by linear Stern-Volmer plots and K(SV) values. Thermodynamic parameters at different temperatures demonstrated that the interaction between c-SWNTs and BSA was mainly favored by hydrophobic force. In addition, Na(+) interfered with the quenching effect of c-SWNTs, which revealed that electrostatic force played a role in binding roles of BSA to c-SWNTs simultaneously. The results of UV and synchronous fluorescence spectrum validated that hydrophobicity of amino acid residues expressly increased with the addition of c-SWNTs. The content of α-helix structure in BSA decreased by 14.06% with c-SWNTs viewed from CD spectrum. Effect of SWNTs on the conformation of BSA could be controlled by the surface chemistry of SWNTs.

Exhaled volatile organic compounds identify patients with colorectal cancer

BACKGROUND

An effective screening tool for colorectal cancer is still lacking. Analysis of the volatile organic compounds (VOCs) linked to cancer is a new frontier in cancer screening, as tumour growth involves several metabolic changes leading to the production of specific compounds that can be detected in exhaled breath. This study investigated whether patients with colorectal cancer have a specific VOC pattern compared with the healthy population.

METHODS

Exhaled breath was collected in an inert bag (Tedlar(®) ) from patients with colorectal cancer and healthy controls (negative at colonoscopy), and processed offline by thermal-desorber gas chromatography-mass spectrometry to evaluate the VOC profile. During the trial phase VOCs of interest were identified and selected, and VOC patterns able to discriminate patients from controls were set up; in the validation phase their discriminant performance was tested on blinded samples. A probabilistic neural network (PNN) validated by the leave-one-out method was used to identify the pattern of VOCs that better discriminated between the two groups.

RESULTS

Some 37 patients and 41 controls were included in the trial phase. Application of a PNN to a pattern of 15 compounds showed a discriminant performance with a sensitivity of 86 per cent, a specificity of 83 per cent and an accuracy of 85 per cent (area under the receiver operating characteristic (ROC) curve 0·852). The accuracy of PNN analysis was confirmed in the validation phase on a further 25 subjects; the model correctly assigned 19 patients, giving an overall accuracy of 76 per cent.

CONCLUSION

The pattern of VOCs in patients with colorectal cancer was different from that in healthy controls. The PNN in this study was able to discriminate patients with colorectal cancer with an accuracy of over 75 per cent. Breath VOC analysis appears to have potential clinical application in colorectal cancer screening, although further studies are required to confirm its reliability in heterogeneous clinical settings.

Detection of Alzheimer’s and Parkinson’s disease from exhaled breath using nanomaterial-based sensors

Aim: To study the feasibility of a novel method in nanomedicine that is based on breath testing for identifying Alzheimer’s disease (AD) and Parkinson’s disease (PD), as representative examples of neurodegenerative conditions. Patients & methods: Alveolar breath was collected from 57 volunteers (AD patients, PD patients and healthy controls) and analyzed using combinations of nanomaterial-based sensors (organically functionalized carbon nanotubes and gold nanoparticles). Discriminant factor analysis was applied to detect statistically significant differences between study groups and classification success was estimated using cross-validation. The pattern identification was supported by chemical analysis of the breath samples using gas chromatography combined with mass spectrometry. Results: The combinations of sensors could clearly distinguish AD from healthy states, PD from healthy states, and AD from PD states, with a classification accuracy of 85, 78 and 84%, respectively. Gas chromatography combined with mass spectrometry analysis showed statistically significant differences in the average abundance of several volatile organic compounds in the breath of AD, PD and healthy subjects, thus supporting the breath prints observed with the sensors. Conclusion: The breath prints that were identified with combinations of nanomaterial-based sensors have future potential as cost-effective, fast and reliable biomarkers for AD and PD.

Original submitted 29 January 2012; Revised submitted 8 May 2012; Published online 15 October 2012

Polycyclic aromatic hydrocarbon for the detection of nonpolar analytes under counteracting humidity conditions

Real-world samples contain reducing and oxidizing chemical agents as well as large and small (bio)molecules, which are polar or nonpolar in nature. Sensing nonpolar analytes, which is of paramount importance for a wide variety of applications, is generally more difficult to achieve than sensing polar analytes. Here, we report on empirical observations of a unique polycyclic aromatic hydrocarbon derivative, referred as PAH-A, whose structure has a triangular-shaped aromatic core (with a carbon number of 60) and contains hydrophobic mesogens terminated with hydrophobic alkyl chains. We show that films made of PAH-A enable excellent sensitivity to nonpolar analytes, compared to polar analytes, in a setting of 5-40% counteracting relative humidity. This finding is based on monitoring the changes in the physical/optical properties of thin PAH-A films upon exposure to nonpolar and polar analytes, by means of quartz crystal microbalance and spectroscopic ellipsometry measurements. A comparison with other polycyclic aromatic hydrocarbon derivatives with different cores or organic functionalities is provided and discussed.

Vectors for inhaled gene therapy in lung cancer. Application for nano oncology and safety of bio nanotechnology

Novel aerosol therapeutic modalities have been investigated for lung cancer. Inhaled gene therapy has presented safety and effectiveness previously in cystic fibrosis. However, safety concerns have been raised regarding the safety of non-viral vectors for inhaled gene therapy in lung cancer, and therefore small steps have been made towards this multifunctional treatment modality. During the last decade, numerous new nanocomplexes have been created and investigated as a safe gene delivery nano-vehicle. These formulations are multifunctional; they can be used as either local therapy or carrier for an effective inhaled gene therapy for lung cancer. Herein, we present current and future perspectives of nanocomplexes for inhaled gene therapy treatment in lung cancer.

Synthesis of nanograined ZnO nanowires and their enhanced gas sensing properties

Polycrystalline ZnO nanowires with grain sizes ranging from 20 to 100 nm were synthesized using a newly designed two-step process: (first step) synthesis of ZnSe nanowires by vapor transportation of a mixture of ZnSe powders; and (second step) thermal oxidation of the ZnSe nanowires at 650 °C. Compared to the single-crystal ZnO nanowire gas sensors and other nanomaterial gas sensors reported previously, the multiple networked nanowire gas sensors fabricated from the nanograined ZnO nanowires showed substantially enhanced electrical responses to NO2 gas at 300 °C. The NO2 gas sensing properties of the nanograined ZnO nanowires increased dramatically with increasing NO2 concentration. The multiple-networked nanograined ZnO nanowire sensor showed a response value of 237,263% at 10 ppm NO2 and 300 °C, whereas the single-crystal ZnO nanowire sensors showed a response of only 6.5% under the same conditions. The recovery time of the nanograined ZnO nanowire sensor was much shorter than that of the normal ZnO nanowire sensor over the NO2 concentration range of 1-10 ppm, even though the response time of the former was somewhat longer than that of the latter. The origin of the enhanced NO2 gas sensing properties of the nanograined ZnO nanowire sensor is discussed.

Detection of asymptomatic nigrostriatal dopaminergic lesion in rats by exhaled air analysis using carbon nanotube sensors

The ante-mortem diagnosis of Parkinson's disease (PD) still relies on clinical symptoms. Biomarkers could in principle be used for the early detection of PD-related neuronal damage, but no validated, inexpensive, and simple biomarkers are available yet. Here we report on the breath-print of presymptomatic PD in rats, using a model with 50% lesion of dopaminergic neurons in substantia nigra. Exhaled breath was collected from 19 rats (10 lesioned and 9 sham operated) and analyzed using organically functionalized carbon nanotube sensors. Discriminant factor analysis detected statistically significant differences between the study groups and a classification accuracy of 90% was achieved using leave-one-out cross-validation. The sensors' breath-print was supported by determining statistically significant differences of several volatile organic compounds in the breath of the lesioned rats and the sham operated rats, using gas chromatography combined with mass spectrometry. The observed breath-print shows potential for cost-effective, fast, and reliable early PD detection.