Artificial noses

Clinical applications of volatilomic assays

The study of metabolomics is revealing immense potential for diagnosis, therapy monitoring, and understanding of pathogenesis processes. Volatilomics is a subcategory of metabolomics interested in the detection of molecules that are small enough to be released in the gas phase. Volatile compounds produced by cellular processes are released into the blood and lymph, and can reach the external environment through different pathways, such as the blood-air interface in the lung that are detected in breath, or the blood-water interface in the kidney that leads to volatile compounds detected in urine. Besides breath and urine, additional sources of volatile compounds such as saliva, blood, feces, and skin are available. Volatilomics traces its roots back over fifty years to the pioneering investigations in the 1970s. Despite extensive research, the field remains in its infancy, hindered by a lack of standardization despite ample experimental evidence. The proliferation of analytical instrumentations, sample preparations and methods of volatilome sampling still make it difficult to compare results from different studies and to establish a common standard approach to volatilomics. This review aims to provide an overview of volatilomics' diagnostic potential, focusing on two key technical aspects: sampling and analysis. Sampling poses a challenge due to the susceptibility of human samples to contamination and confounding factors from various sources like the environment and lifestyle. The discussion then delves into targeted and untargeted approaches in volatilomics. Some case studies are presented to exemplify the results obtained so far. Finally, the review concludes with a discussion on the necessary steps to fully integrate volatilomics into clinical practice.

Volatile Organic Compound Sensing Array and Optoelectronic Filter System using Ion-Pairing Dyes with a Wide Visible Spectrum

An ideal dye-based sensing array has essential design requirements, including facile preparation methodology, tolerance to water vapor, a broad range of color-responsive changes, and a simple readout system. Here, a brief synthetic route is developed for ion-pairing dyes exhibiting unusual chromatic changes across the entire visible spectrum. It requires only mixing and precipitation under mild conditions. The dyes are applied to a sensing array containing 12 sensing elements with different initial states. Owing to the numerous color variations of the dyes, the color map generated by the array is highly simple yet sufficiently accurate to distinguish among the different functional groups (such as amines, aldehydes, and carboxylic acids) as well as carbon chain lengths. Principle component analysis (PCA) demonstrates that volatile organic compounds (VOCs) can be well classified according to the color changes of the sensing array. The ion-pairing dyes are embedded into 3D stacked nanofibers via electrospinning, and function as effective harmful-gas (e.g., formaldehyde) sensors with sub-ppm theoretical detection limits (0.15 ppm). Finally, the 3D stacked nanofibers can be employed in an optoelectronic filter system that automatically checks for formaldehyde in the surroundings and also confirms the effective removal of the detected formaldehyde by the gas filter cartridge.

Canine Smell Preferences—Do Dogs Have Their Favorite Scents?

Simple Summary

There are many products that are targeted to pet owners. One category of these products is dog repellents—strongly aromatized solutions designed to stop dogs from approaching and investigating particular areas; the second are cosmetics which should be pleasant for dogs. Dogs have a particularly sensitive sense of smell; therefore, strong scents may be very intense, and not always pleasant, stimuli. It is truly interesting, then, that canine cosmetic products often have very strong fragrances designed mostly to appeal to the dog owners, rather than to the dogs themselves. Indeed, the scents that dogs choose to put on their fur differ strongly from those of common cosmetics. Dogs choose mostly intense, animal-derived smells, such as feces or carcasses, so there is a need to differentiate between canine and human smell preferences. As there is limited scientific data related to canine smell preferences, the purpose of this study was to verify dogs’ reactions to selected scents, which can also be appealing to humans. Our study shows that dogs were more likely to interact with the scents of blueberry, blackberry, mint, rose, lavender, and linalol.

Abstract

The available evidence on dogs’ scent preferences is quite limited. The purpose of this study was to verify the canine response to selected odors that may also be preferred by humans. The experiment was performed using 14 adult dogs (10 female and 4 male) of different breeds, body size, and age (1–14 years). During the experiment, dogs were exposed to 33 odor samples: a neutral sample containing pure dipropylene glycol (control) and 32 samples containing dipropylene glycol and fragrance oils. The dog was brought to the experimental area by its handler, who then stopped at the entrance, unleashed the dog, and remained in the starting position. The dog freely explored the area for 30 s. All dog movements and behavior were recorded and analyzed. The methodology of observing the dogs freely exploring the experimental area allowed us to determine the smells that were the most attractive to them (food, beaver clothing). Our study shows that dogs interacted more frequently with the scents of blueberries, blackberries, mint, rose, lavender, and linalol.

Sensors for Volatile Organic Compounds

This paper provides an overview of recent developments in the field of volatile organic compound (VOC) sensors, which are finding uses in healthcare, safety, environmental monitoring, food and agriculture, oil industry, and other fields. It starts by briefly explaining the basics of VOC sensing and reviewing the currently available and quickly progressing VOC sensing approaches. It then discusses the main trends in materials' design with special attention to nanostructuring and nanohybridization. Emerging sensing materials and strategies are highlighted and their involvement in the different types of sensing technologies is discussed, including optical, electrical, and gravimetric sensors. The review also provides detailed discussions about the main limitations of the field and offers potential solutions. The status of the field and suggestions of promising directions for future development are summarized.

Canine Olfaction: Physiology, Behavior, and Possibilities for Practical Applications

Simple Summary

Dogs have an extraordinary olfactory capability, which far exceeds that of humans. Dogs’ sense of smell seems to be the main sense, allowing them to not only gather both current and historical information about their surrounding environment, but also to find the source of the smell, which is crucial for locating food, danger, or partners for reproduction. Dogs can be trained by humans to use their olfactory abilities in a variety of fields, with a detection limit often much lower than that of sophisticated laboratory instruments. The specific anatomical and physiological features of dog olfaction allow humans to achieve outstanding results in the detection of drugs, explosives, and different illnesses, such as cancer, diabetes, or infectious disease. This article provides an overview of the anatomical features and physiological mechanisms involved in the process of odor detection and identification, as well as behavioral aspects of canine olfaction and its use in the service of humans in many fields.

Abstract

Olfaction in dogs is crucial for gathering important information about the environment, recognizing individuals, making decisions, and learning. It is far more specialized and sensitive than humans’ sense of smell. Using the strength of dogs’ sense of smell, humans work with dogs for the recognition of different odors, with a precision far exceeding the analytical capabilities of most modern instruments. Due to their extremely sensitive sense of smell, dogs could be used as modern, super-sensitive mobile area scanners, detecting specific chemical signals in real time in various environments outside the laboratory, and then tracking the odor of dynamic targets to their source, also in crowded places. Recent studies show that dogs can detect not only specific scents of drugs or explosives, but also changes in emotions as well as in human cell metabolism during various illnesses, including COVID-19 infection. Here, we provide an overview of canine olfaction, discussing aspects connected with anatomy, physiology, behavioral aspects of sniffing, and factors influencing the olfactory abilities of the domestic dog (Canis familiaris).

Principles of odor coding in vertebrates and artificial chemosensory systems

The biological olfactory system is the sensory system responsible for the detection of the chemical composition of the environment. Several attempts to mimic biological olfactory systems have led to various artificial olfactory systems using different technical approaches. Here we provide a parallel description of biological olfactory systems and their technical counterparts. We start with a presentation of the input to the systems, the stimuli, and treat the interface between the external world and the environment where receptor neurons or artificial chemosensors reside. We then delineate the functions of receptor neurons and chemosensors as well as their overall I-O relationships. Up to this point, our account of the systems goes along similar lines. The next processing steps differ considerably: while in biology the processing step following the receptor neurons is the "integration" and "processing" of receptor neuron outputs in the olfactory bulb, this step has various realizations in electronic noses. For a long period of time, the signal processing stages beyond the olfactory bulb, i.e., the higher olfactory centers were little studied. Only recently there has been a marked growth of studies tackling the information processing in these centers. In electronic noses, a third stage of processing has virtually never been considered. In this review, we provide an up-to-date overview of the current knowledge of both fields and, for the first time, attempt to tie them together. We hope it will be a breeding ground for better information, communication, and data exchange between very related but so far little connected fields.

The Optoelectronic Nose

How does one tell the difference between one molecule or mixture of molecules from another? Chemical sensing seeks to probe physical or chemical properties of molecular or ionic species (i.e., analytes) and transform that information into a useful and distinguishable output. The olfactory system of animals is the prototype of chemical sensing. Even for human beings (who are generally more visual than olfactory creatures), the sense of smell is one of our most basic capabilities, and we can discriminate among many thousands, and possibly even billions, of different odors. The chemical specificity of the olfactory system does not come from specific receptors for specific analytes (i.e., the traditional lock-and-key model of enzyme-substrate interactions), but rather olfaction uses pattern recognition of the combined responses of several hundred olfactory receptors.In analogy to olfaction, colorimetric sensor arrays provide high dimensional data from the color changes of chemically responsive colorants as they are exposed to analytes. These colorants include pH responsive dyes, Lewis acid/base indicators, redox dyes, vapochromics, and surface-modified silver nanoparticles. The color difference maps so created provide chemical sensing with high sensitivity (often down to ppb levels), impressive discrimination among very similar analytes, and exquisite fingerprinting of extremely similar mixtures over a wide range of analyte types, both in the gas and liquid phases. Such colorimetric arrays probe a wide range of the chemical reactivity of analytes, rather than the limited dimensionality of physical properties (e.g., mass) or physisorption (e.g., traditional electronic noses). Our sensor arrays are disposable and simple to produce by either inkjet or robotic dip-pen printing onto the surface of porous polymer membranes or even paper.Design of both sensor arrays and optical readers for their analysis has advanced to a fully self-contained pocket-sized instrument, the optoelectronic nose. Quantitative analysis requires appropriate chemometric methods for pattern recognition of data with inherently high dimensionality, e.g., hierarchical cluster analysis and support vector machines. A wide range of applications for the colorimetric sensor arrays has been developed, including personal dosimetry of toxic industrial chemicals, detection of explosives or fire accelerants, monitoring pollutants for artwork and cultural heritage preservation, quality control of foods and beverages, rapid identification of bacteria and fungi, and detection of disease biomarkers in breath or urine. The development of portable, high-accuracy instrumentation using standard imaging devices with the capability of onboard, real-time analysis has had substantial progress and increasingly meets the expectations for real-world use.

Sensor-Array Optimization Based on Time-Series Data Analytics for Sanitation-Related Malodor Detection

There is an unmet need for a low-cost instrumented technology for detecting sanitation-related malodor as an alert for maintenance around shared toilets and emerging technologies for onsite waste treatment. In this article, our approach to an electronic nose for sanitation-related malodor is based on the use of electrochemical gas sensors, and machine-learning techniques for sensor selection and odor classification. We screened 10 sensors from different vendors with specific target gases and recorded their response to malodor from fecal specimens and urine specimens, and confounding good odors such as popcorn. The analysis of 180 odor exposures data by two feature-selection methods based on mutual information indicates that, for malodor detection, the decision tree (DT) classifier with seven features from four sensors provides 88.0% balanced accuracy and 85.1% macro F1 score. However, the k-nearest-neighbors (KNN) classifier with only three features (from two sensors) obtains 83.3% balanced accuracy and 81.3% macro F1 score. For classification of urine against feces malodor, a balanced accuracy of 94.0% and a macro F1 score of 92.9% are achieved using only four features from three sensors and a logistic regression (LR) classifier.

Cross-Reactive, Self-Encoded Polymer Film Arrays for Sensor Applications

The development of chemical sensors continues to be an active area of research, especially the development of a practical electronic nose. Here, we present a spectroscopic chemical sensor based on an array of 64 self-encoded polymer films deposited on a microfabricated silicon substrate. The polymer arrays were analyzed by FTIR and Raman spectroscopy before and after exposure to a series of organic volatiles to monitor changes in their vibrational fingerprints. We show here that the spectroscopic changes of self-encoded polymer films can be used to distinguish between volatile organic analytes. Changes induced in the sensor arrays by the analyte vapor were denoted by a spectroscopic response of the self-encoded polymer sensors and transformed into a response pattern by multivariate data analysis using partial least squares regression. The results indicated that the polymer sensors provide a unique and reproducible pattern for each analyte vapor and can potentially be used in the fabrication of a novel electronic nose device.

Development of a Column-Shaped Fluorometric Sensor Array and Its Application in Visual Discrimination of Alcohols from Vapor Phase

Portable, miniaturized, and inexpensive detectors are in high demand for detecting and discriminating volatile organic compounds (VOCs). Sensor array design and exploitation are two key issues for new detector development. In contrast to the most reported plane-shaped sensor array for gaseous analyte sensing, here we report a column-shaped fluorometric sensor array by using fluorophore-loaded silica particles (∼40 μm) filled capillary. In the design, the capillary serves as test chamber and facilitates visualization. The orifices of the capillary were used as inlet and outlet for gaseous analyte. Sensing modules are installed in series, which lays foundation for their even and effective contact with the gaseous analyte. Meanwhile, further capsulation could be avoided. Silica particles were chosen as carries due to their preferred adsorption behavior to VOCs. By choosing four typical fluorophores (PBI-CB, Py-CB-Ph, Py-At, and NA-Ch) as sensing units, a 4-element fluorometric sensor array was achieved. Fluorescence of the array varied when different alcohol vapors were pumped in. The six tested alcohols could not only be distinguished as primary, secondary, or tertiary, but also be identified individually. The array had good reproducibility in visualization of the six alcohols. In addition, the orders of the fluorophores can be changed as desired. It is believed that the proofed concept provides not only a totally new design of sensor array but also contributes a new strategy for the discrimination of the alcohols as examined.

Simultaneous Proton Transfer Reaction-Mass Spectrometry and electronic nose study of the volatile compounds released by Plasmodium falciparum infected red blood cells in vitro

The discovery that Volatile Organic Compounds (VOCs) can be biomarkers for several diseases has led to the conception of their possible application as diagnostic tools. In this study, we aimed at defining of diagnostic signatures for the presence of malaria transmissible stages in infected individuals. To do this, we compared VOCs released by asexual and sexual stage cultures of Plasmodium falciparum, the deadliest species of malaria, with those emitted by uninfected red blood cells (RBCs). VOC analysis was carried out with an innovative set-up, where each sample was simultaneously analysed by proton transfer reaction time of flight mass spectrometry (PTR-ToF-MS) and an electronic nose. PTR-Tof-MS results show that sexual stages are characterized by a larger emission of hexanal, compared with uninfected or asexual stage-infected RBCs, which makes them clearly identifiable. PTR-Tof-MS analysis also detected differences in VOC composition between asexual stages and uninfected RBCs. These results have been substantially replicated by the electronic nose analysis and may open the possibility to develop sensitive and easy-to-use devices able to detect sexual parasite stages in infected individuals. This study also demonstrates that the combination of mass spectrometry with electronic noses is a useful tool to identify markers of diseases and to support the development of optimized sensors.

Odorant-Binding Proteins as Sensing Elements for Odour Monitoring

Odour perception has been the object of fast growing research interest in the last three decades. Parallel to the study of the corresponding biological systems, attempts are being made to model the olfactory system with electronic devices. Such projects range from the fabrication of individual sensors, tuned to specific chemicals of interest, to the design of multipurpose smell detectors using arrays of sensors assembled in a sort of artificial nose. Recently, proteins have attracted increasing interest as sensing elements. In particular, soluble olfaction proteins, including odorant-binding proteins (OBPs) of vertebrates and insects, chemosensory proteins (CSPs) and Niemann-Pick type C2 (NPC2) proteins possess interesting characteristics for their use in sensing devices for odours. In fact, thanks to their compact structure, their soluble nature and small size, they are extremely stable to high temperature, refractory to proteolysis and resistant to organic solvents. Moreover, thanks to the availability of many structures solved both as apo-proteins and in complexes with some ligands, it is feasible to design mutants by replacing residues in the binding sites with the aim of synthesising proteins with better selectivity and improved physical properties, as demonstrated in a number of cases.

Highly-sensitive optical organic vapor sensor through polymeric swelling induced variation of fluorescent intensity

Traditional optical organic vapor sensors with solvatochromic shift mechanisms have lower sensitivity due to weak intermolecular interactions. Here, we report a general strategy to prepare a higher sensitivity optical organic vapor sensor through polymeric swelling-induced variation of fluorescent intensity. We combine one-dimensional polymeric structures and aggregation-induced emission (AIE) molecules together to form a polymer/AIE microwires array as a sensor. The prepared sensors based on different commercial polymers can successfully classify and identify various organic vapors. Among them, the poly(vinyl butyral)/AIE microwires array can detect methanol vapor as low as 0.05% of its saturation vapor pressure. According to the theory of like dissolves like, we further fabricate a polymer/AIE microwires array derived from designable polyethersulfones, through regulating their side chains, to distinguish similar organic vapors of benzene and toluene. Both experimental and theoretical simulation results reveal that specific molecular interactions between the polyethersulfones and organic vapors can improve the specific recognition performance of the sensors.

From Gas Sensors to Biomimetic Artificial Noses

Since the first attempts to mimic the human nose with artificial devices, a variety of sensors have been developed, ranging from simple inorganic and organic gas detectors to biosensing elements incorporating proteins of the biological olfactory system. In order to design a device able to mimic the human nose, two major issues still need to be addressed regarding the complexity of olfactory coding and the extreme sensitivity of the biological system. So far, only 50 of the approximately 300–400 functioning olfactory receptors have been de-orphanized, still a long way from breaking the human olfactory code. On the other hand, the exceptional sensitivity of the human nose is based on amplification mechanisms difficult to reproduce with electronic circuits, and perhaps novel approaches are required to address this issue. Here, we review the recent literature on chemical sensing both in biological systems and artificial devices, and try to establish the state-of-the-art towards the design of an electronic nose.

Chemically mediated species recognition in two sympatric Grayling butterflies: Hipparchia fagi and Hipparchia hermione (Lepidoptera: Nymphalidae, Satyrinae)

Pheromones are known to play an important role in butterfly courtship and may influence both individual reproductive success and reproductive isolation between species. Recent studies have focused on courtship in Hipparchia butterflies (Nymphalidae: Satyrinae) emphasizing morphological and behavioural traits, as well as genetic differences. Behavioural observations suggested a role for chemical cues in mate and species recognition, where the androconial scales on the forewings of these species may be involved in chemical communication between individuals. Cchemical-mediated signals have received relatively little attention in this genus. Here, we report the results of a three-year investigation of the volatile organic compounds (VOCs) released by Hipparchia fagi and H. hermione in order to identify differences in VOCs between these species where they live in syntopy. Our study was carried out using an array of cross-selective sensors known as an "Electronic Nose" (EN) that operates by converting chemical patterns into patterns of sensor signals. While the identity of volatile compounds remained unknown, sensor signals can be compared to identify similar or dissimilar chemical patterns. Based on the EN signals, our results showed that: 1) the two sexes have a similar VOCs pattern in H. fagi, while they significantly diverge in H. hermione; 2) VOCs patterns were different between females of the two species, while those of males were not.

Identification of aminoglycoside antibiotics in milk matrix with a colorimetric sensor array and pattern recognition methods

Aminoglycoside antibiotics (AAs) abused in animal husbandry can cause antibiotic residues in animal-derived foods, which do harm to human beings' health. Therefore the detection of AAs residues in the animal-origin foods, such as milk, eggs and meat is necessary. We used two single-stranded DNA (ssDNA) oligonucleotides as nonspecific receptors to develop a simple colorimetric sensor array based on gold nanoparticles (AuNPs) for identification and quantification the AAs. Different AA addition triggered the DNA detaching from AuNPs then resulted in different degree salt induced aggregation of AuNPs. The aggregation induced spectral changes of AuNPs with five AA addition were analyzed based on pattern recognition techniques, fisher linear discriminant analysis (FLD) and hierarchical cluster analysis (HCA). The results indicated that colorimetric sensor array has successfully identified five AAs at a concentration range of 120-280 nM. Five AAs in aqueous solution and complex milk matrix can be identified with an accuracy of 100%. More importantly, our developed sensor array is sufficiently sensitive for the discrimination of pure streptomycin (STR), binary mixtures of STR and gentamicin (GEN) at a total concentration of 120 nM.

Towards scanning probe lithography-based 4D nanoprinting by advancing surface chemistry, nanopatterning strategies, and characterization protocols

Biointerfaces direct some of the most complex biological events, including cell differentiation, hierarchical organization, and disease progression, or are responsible for the remarkable optical, electronic, and biological behavior of natural materials. Chemical information encoded within the 4D nanostructure of biointerfaces - comprised of the three Cartesian coordinates (x, y, z), and chemical composition of each molecule within a given volume - dominates their interfacial properties. As such, there is a strong interest in creating printing platforms that can emulate the 4D nanostructure - including both the chemical composition and architectural complexity - of biointerfaces. Current nanolithography technologies are unable to recreate 4D nanostructures with the chemical or architectural complexity of their biological counterparts because of their inability to position organic molecules in three dimensions and with sub-1 micrometer resolution. Achieving this level of control over the interfacial structure requires transformational advances in three complementary research disciplines: (1) the scope of organic reactions that can be successfully carried out on surfaces must be increased, (2) lithography tools are needed that are capable of positioning soft organic and biologically active materials with sub-1 micrometer resolution over feature diameter, feature-to-feature spacing, and height, and (3) new techniques for characterizing the 4D structure of interfaces should be developed and validated. This review will discuss recent advances in these three areas, and how their convergence is leading to a revolution in 4D nanomanufacturing.

Cutting Edge Methods for Non-Invasive Disease Diagnosis Using E-Tongue and E-Nose Devices

Biomimetic cross-reactive sensor arrays (B-CRSAs) have been used to detect and diagnose a wide variety of diseases including metabolic disorders, mental health diseases, and cancer by analyzing both vapor and liquid patient samples. Technological advancements over the past decade have made these systems selective, sensitive, and affordable. To date, devices for non-invasive and accurate disease diagnosis have seen rapid improvement, suggesting a feasible alternative to current standards for medical diagnostics. This review provides an overview of the most recent B-CRSAs for diagnostics (also referred to electronic noses and tongues in the literature) and an outlook for future technological development.

A preliminary analysis of volatile metabolites of human induced pluripotent stem cells along the in vitro differentiation

Cellular metabolism of stem cell biology is still an unexplored field. However, considering the amount of information carried by metabolomes, this is a promising field for a fast identification of stem cells itself and during the differentiation process. One of the goals of such application is the identification of residual pluripotent cells before cell transplantation to avoid the occurrence of teratomas. In this paper, we investigated in vitro the volatile compounds (VOCs) released during human induced pluripotent stem cells (hiPSCs) reprogramming. In particular, we studied hiPSCs differentiation to floating and adherent embryoid bodies until early neural progenitor cells. A preliminary Gas Chromatographic/Mass Spectrometer (GC/MS) analysis, based on a single extraction method and chromatographic separation, indicated 17 volatile compounds whose relative abundance is altered in each step of the differentiation process. The pattern of VOCs shown by hiPSCs is well distinct and makes these cells sharply separated from the other steps of differentiations. Similar behaviour has also been observed with an array of metalloporphyrins based gas sensors. The use of electronic sensors to control the process of differentiation of pluripotent stem cells might suggest a novel perspective for a fast and on-line control of differentiation processes.

Capillarity-based preparation system for optical colorimetric sensor arrays

In recent years, optical colorimetric sensor arrays have demonstrated beneficial features, including rapid response, high selectivity, and high specificity; as a result, it has been extensively applied in food inspection and chemical studies, among other fields. There are instruments in the current market available for the preparation of an optical colorimetric sensor array, but it lacks the corresponding research of the preparation mechanism. Therefore, in connection with the main features of this kind of sensor array such as consistency, based on the preparation method of contact spotting, combined with a capillary fluid model, Washburn equation, Laplace equation, etc., this paper develops a diffusion model of an optical colorimetric sensor array during its preparation and sets up an optical colorimetric sensor array preparation system based on this diffusion model. Finally, this paper compares and evaluates the sensor arrays prepared by the system and prepared manually in three aspects such as the quality of array point, response of array, and response result, and the results show that the performance index of the sensor array prepared by a system under this diffusion model is better than that of the sensor array of manual spotting, which meets the needs of the experiment.

Toward high value sensing: monolayer-protected metal nanoparticles in multivariable gas and vapor sensors

This review provides analysis of advances in multivariable sensors based on monolayer-protected nanoparticles and several principles of signal transduction that result in building non-resonant and resonant electrical sensors as well as material- and structure-based photonic sensors.

Surface tension sensor meshes for rapid alcohol quantification

Electrospun polymeric sensor arrays detect alcohol content in wine via changes in surface tension.

Discrimination of American ginseng and Asian ginseng using electronic nose and gas chromatography-mass spectrometry coupled with chemometrics

BACKGROUND

American ginseng (Panax quinquefolius L.) and Asian ginseng (Panax ginseng Meyer) products, such as slices, have a similar appearance, but they have significantly different prices, leading to widespread adulteration in the commercial market. Their aroma characteristics are attracting increasing attention and are supposed to be effective and nondestructive markers to determine adulteration.

METHODS

The aroma characteristics of American and Asian ginseng were investigated using gas chromatography-mass spectrometry(GC-MS) and an electronic nose (E-nose). Their volatile organic compounds were separated, classified, compared, and analyzed with different pattern recognition.

RESULTS

The E-nose showed a good performance in grouping with a principle component analysis explaining 94.45% of variance. A total of 69 aroma components were identified by GC-MS, with 35.6% common components and 64.6% special ingredients between the two ginsengs. It was observed that the components and the number of terpenes and alcohols were markedly different, indicating possible reasons for their difference. The results of pattern recognition confirmed that the E-nose processing result is similar to that of GC-MS. The interrelation between aroma constituents and sensors indicated that special sensors were highly related to some terpenes and alcohols. Accordingly, the contents of selected constituents were accurately predicted by corresponding sensors with most R2 reaching 90%.

CONCLUSION

Combined with advanced chemometrics, the E-nose is capable of discriminating between American and Asian ginseng in both qualitative and quantitative angles, presenting an accurate, rapid, and nondestructive reference approach.

Toward wearable sensors: optical sensor for detection of ammonium nitrate-based explosives, ANFO and ANNM

An imine-functionalized polymer displays selective fluorimetric response to the component of ANFO and ANNM, ammonium nitrate and nitromethane!

Binary coded identification of industrial chemical vapors with an optofluidic nose

An artificial nose system for the recognition and classification of gas-phase analytes and its application in identifying common industrial gases is reported. The sensing mechanism of the device comprises the measurement of infrared absorption of volatile analytes inside the hollow cores of optofluidic Bragg fibers. An array of six fibers is used, where each fiber targets a different region of the mid-infrared in the range of 2-14 μm with transmission bandwidths of about 1-3 μm. The quenching in the transmission of each fiber due to the presence of analyte molecules in the hollow core is measured separately and the cross response of the array allows the identification of virtually any volatile organic compound (VOC). The device was used for the identification of seven industrial VOC vapors with high selectivity using a standard blackbody source and an infrared detector. The array response is registered as a unique six digit binary code for each analyte by assigning a threshold value to the fiber transmissions. The developed prototype is a comprehensive and versatile artificial nose that is applicable to a wide range of analytes.

Normalized Neural Representations of Complex Odors

The olfactory system removes correlations in natural odors using a network of inhibitory neurons in the olfactory bulb. It has been proposed that this network integrates the response from all olfactory receptors and inhibits them equally. However, how such global inhibition influences the neural representations of odors is unclear. Here, we study a simple statistical model of the processing in the olfactory bulb, which leads to concentration-invariant, sparse representations of the odor composition. We show that the inhibition strength can be tuned to obtain sparse representations that are still useful to discriminate odors that vary in relative concentration, size, and composition. The model reveals two generic consequences of global inhibition: (i) odors with many molecular species are more difficult to discriminate and (ii) receptor arrays with heterogeneous sensitivities perform badly. Comparing these predictions to experiments will help us to understand the role of global inhibition in shaping normalized odor representations in the olfactory bulb.

Biomimetic Cross-Reactive Sensor Arrays: Prospects in Biodiagnostics

Biomimetic cross-reactive sensor arrays have been used to detect and analyze a wide variety of vapour and liquid components in applications such as food science, public health and safety, and diagnostics. As technology has advanced over the past three decades, these systems have become selective, sensitive, and affordable. Currently, the need for non-invasive and accurate devices for early disease diagnosis remains a challenge. This review provides an overview of the various types of Biomimetic cross-reactive sensor arrays (also referred to as electronic noses and tongues in the literature), their current use and future directions, and an outlook for future technological development.

Rapid Quantification of Trimethylamine

Sensitive detection of trimethylamine both in aqueous and gaseous phases has been accomplished using an inexpensive colorimetric sensor array. Distinctive color change patterns provide facile discrimination over a wide range of concentrations for trimethylamine with >99% accuracy of classification. Calculated limits of detection are well below the diagnostically significant concentration for trimethylaminuria (fish malodor syndrome). The sensor array shows good reversibility after multiple uses and is able to cleanly discriminate trimethylamine from similar amine odorants. Portable sensing of trimethylamine vapors at ppb concentrations is described using a cell phone camera or a hand-held optoelectronic nose. Application of the sensor array in detecting mouth and skin odor as a potential tool for portable diagnosis of trimethylaminuria is also illustrated.

Receptor arrays optimized for natural odor statistics

Natural odors typically consist of many molecules at different concentrations. It is unclear how the numerous odorant molecules and their possible mixtures are discriminated by relatively few olfactory receptors. Using an information theoretic model, we show that a receptor array is optimal for this task if it achieves two possibly conflicting goals: (i) Each receptor should respond to half of all odors and (ii) the response of different receptors should be uncorrelated when averaged over odors presented with natural statistics. We use these design principles to predict statistics of the affinities between receptors and odorant molecules for a broad class of odor statistics. We also show that optimal receptor arrays can be tuned to either resolve concentrations well or distinguish mixtures reliably. Finally, we use our results to predict properties of experimentally measured receptor arrays. Our work can thus be used to better understand natural olfaction, and it also suggests ways to improve artificial sensor arrays.

Identification of a Large Pool of Microorganisms with an Array of Porphyrin Based Gas Sensors

The association between volatile compounds (VCs) and microorganisms, as demonstrated by several studies, may offer the ground for a rapid identification of pathogens. To this regard, chemical sensors are a key enabling technology for the exploitation of this opportunity. In this study, we investigated the performance of an array of porphyrin-coated quartz microbalance gas sensors in the identification of a panel of 12 bacteria and fungi. The porphyrins were metal complexes and the free base of a functionalized tetraphenylporphyrin. Our results show that the sensor array distinguishes the VC patterns produced by microorganisms in vitro. Besides being individually identified, bacteria are also sorted into Gram-positive and Gram-negative.

An optoelectronic nose for identification of explosives

Compact and portable methods for identification of explosives are increasingly needed for both civilian and military applications. A portable optoelectronic nose for the gas-phase identification of explosive materials is described that uses a highly cross-reactive colorimetric sensor array and a handheld scanner. The array probes a wide range of chemical reactivities using 40 chemically responsive colorimetric indicators, including pH sensors, metal-dye salts, redox-sensitive chromogenic compounds, solvatochromic dyes, and other chromogenic indicators. Sixteen separate analytes including common explosives, homemade explosives, and characteristic explosive components were differentiated into fourteen separate classes with a classification error rate of <1%. Portable colorimetric array sensing could represent an important, complementary part of the toolbox used in practical applications of explosives detection and identification.

The lung cancer breath signature: a comparative analysis of exhaled breath and air sampled from inside the lungs

Results collected in more than 20 years of studies suggest a relationship between the volatile organic compounds exhaled in breath and lung cancer. However, the origin of these compounds is still not completely elucidated. In spite of the simplistic vision that cancerous tissues in lungs directly emit the volatile metabolites into the airways, some papers point out that metabolites are collected by the blood and then exchanged at the air-blood interface in the lung. To shed light on this subject we performed an experiment collecting both the breath and the air inside both the lungs with a modified bronchoscopic probe. The samples were measured with a gas chromatography-mass spectrometer (GC-MS) and an electronic nose. We found that the diagnostic capability of the electronic nose does not depend on the presence of cancer in the sampled lung, reaching in both cases an above 90% correct classification rate between cancer and non-cancer samples. On the other hand, multivariate analysis of GC-MS achieved a correct classification rate between the two lungs of only 76%. GC-MS analysis of breath and air sampled from the lungs demonstrates a substantial preservation of the VOCs pattern from inside the lung to the exhaled breath.

Differential sensing for the regio- and stereoselective identification and quantitation of glycerides

Glycerides are of interest to the areas of food science and medicine because they are the main component of fat. From a chemical sensing perspective, glycerides are challenging analytes because they are structurally similar to one another and lack diversity in terms of functional groups. Furthermore, because animal and plant fat consists of a number of stereo- and regioisomeric acylglycerols, their components remain challenging analytes for chromatographic and mass spectrometric determination, particularly the quantitation of species in mixtures. In this study, we demonstrated the use of an array of cross-reactive serum albumins and fluorescent indicators with chemometric analysis to differentiate a panel of mono-, di-, and triglycerides. Due to the difficulties in identifying the regio- and stereochemistry of the unsaturated glycerides, a sample pretreatment consisting of olefin cross-metathesis with an allyl fluorescein species was used before array analysis. Using this simple assay, we successfully discriminated 20 glycerides via principal component analysis and linear discriminant analysis (PCA and LDA, respectively), including stereo- and regioisomeric pairs. The resulting chemometric patterns were used as a training space for which the structural characteristics of unknown glycerides were identified. In addition, by using our array to perform a standard addition analysis on a mixture of triglycerides and using a method introduced herein, we demonstrated the ability to quantitate glyceride components in a mixture.

Stable odor recognition by a neuro-adaptive electronic nose

Sensitivity, selectivity and stability are decisive properties of sensors. In chemical gas sensors odor recognition can be severely compromised by poor signal stability, particularly in real life applications where the sensors are exposed to unpredictable sequences of odors under changing external conditions. Although olfactory receptor neurons in the nose face similar stimulus sequences under likewise changing conditions, odor recognition is very stable and odorants can be reliably identified independently from past odor perception. We postulate that appropriate pre-processing of the output signals of chemical sensors substantially contributes to the stability of odor recognition, in spite of marked sensor instabilities. To investigate this hypothesis, we use an adaptive, unsupervised neural network inspired by the glomerular input circuitry of the olfactory bulb. Essentially the model reduces the effect of the sensors’ instabilities by utilizing them via an adaptive multicompartment feed-forward inhibition. We collected and analyzed responses of a 4 × 4 gas sensor array to a number of volatile compounds applied over a period of 18 months, whereby every sensor was sampled episodically. The network conferred excellent stability to the compounds’ identification and was clearly superior over standard classifiers, even when one of the sensors exhibited random fluctuations or stopped working at all.

Corroles-porphyrins: a teamwork for gas sensor arrays

Porphyrins provide an excellent material for chemical sensors, and they have been used for sensing species both in air and solution. In the gas phase, the broad selectivity of porphyrins is largely dependant on molecular features, such as the metal ion complexed at the core of the aromatic ring and the peripheral substituents. Although these features have been largely exploited to design gas sensor arrays, so far, little attention has been devoted to modify the sensing properties of these macrocycles by variation of the molecular aromatic ring. In this paper, the gas sensing properties of a porphyrin analog, the corrole, are studied in comparison with those of the parent porphyrin. Results show that changes in the aromatic ring have important consequences on the sensitivity and selectivity of the sensors and that porphyrins and corroles can positively cooperate to enhance the performance of sensor arrays.

Drosophila olfactory receptors as classifiers for volatiles from disparate real world applications

Olfactory receptors evolved to provide animals with ecologically and behaviourally relevant information. The resulting extreme sensitivity and discrimination has proven useful to humans, who have therefore co-opted some animals' sense of smell. One aim of machine olfaction research is to replace the use of animal noses and one avenue of such research aims to incorporate olfactory receptors into artificial noses. Here, we investigate how well the olfactory receptors of the fruit fly, Drosophila melanogaster, perform in classifying volatile odourants that they would not normally encounter. We collected a large number of in vivo recordings from individual Drosophila olfactory receptor neurons in response to an ecologically relevant set of 36 chemicals related to wine ('wine set') and an ecologically irrelevant set of 35 chemicals related to chemical hazards ('industrial set'), each chemical at a single concentration. Resampled response sets were used to classify the chemicals against all others within each set, using a standard linear support vector machine classifier and a wrapper approach. Drosophila receptors appear highly capable of distinguishing chemicals that they have not evolved to process. In contrast to previous work with metal oxide sensors, Drosophila receptors achieved the best recognition accuracy if the outputs of all 20 receptor types were used.

Feasibility of Energy-Autonomous Wireless Microsensors for Biomedical Applications: Powering and Communication

In this review, biomedical-related wireless miniature devices such as implantable medical devices, neural prostheses, embedded neural systems, and body area network systems are investigated and categorized. The two main subsystems of such designs, the RF subsystem and the energy source subsystem, are studied in detail. Different application classes are considered separately, focusing on their specific data rate and size characteristics. Also, the energy consumption of state-of-the-art communication practices is compared to the energy that can be generated by current energy scavenging devices, highlighting gaps and opportunities. The RF subsystem is classified, and the suitable architecture for each category of applications is highlighted. Finally, a new figure of merit suitable for wireless biomedical applications is introduced to measure the performance of these devices and assist the designer in selecting the proper system for the required application. This figure of merit can effectively fill the gap of a much required method for comparing different techniques in simulation stage before a final design is chosen for implementation.

Demonstration of fast and accurate discrimination and quantification of chemically similar species utilizing a single cross-selective chemiresistor

Performance characteristics of gas-phase microsensors will determine the ultimate utility of these devices for a wide range of chemical monitoring applications. Commonly employed chemiresistor elements are quite sensitive to selected analytes, and relatively new methods have increased the selectivity to specific compounds, even in the presence of interfering species. Here, we have focused on determining whether purposefully driven temperature modulation can produce faster sensor-response characteristics, which could enable measurements for a broader range of applications involving dynamic compositional analysis. We investigated the response speed of a single chemiresitive In2O3 microhotplate sensor to four analytes (methanol, ethanol, acetone, 2-butanone) by systematically varying the oscillating frequency (semicycle periods of 20-120 ms) of a bilevel temperature cycle applied to the sensing element. It was determined that the fastest response (≈ 9 s), as indicated by a 98% signal-change metric, occurred for a period of 30 ms and that responses under such modulation were dramatically faster than for isothermal operation of the same device (>300 s). Rapid modulation between 150 and 450 °C exerts kinetic control over transient processes, including adsorption, desorption, diffusion, and reaction phenomena, which are important for charge transfer occurring in transduction processes and the observed response times. We also demonstrate that the fastest operation is accompanied by excellent discrimination within a challenging 16-category recognition problem (consisting of the four analytes at four separate concentrations). This critical finding demonstrates that both speed and high discriminatory capabilities can be realized through temperature modulation.

Optical sensor arrays for chemical sensing: the optoelectronic nose

A comprehensive review is presented on the development and state of the art of colorimetric and fluorometric sensor arrays. Optical arrays based on chemoresponsive colorants (dyes and nanoporous pigments) probe the chemical reactivity of analytes, rather than their physical properties. This provides a high dimensionality to chemical sensing that permits high sensitivity (often down to ppb levels), impressive discrimination among very similar analytes and exquisite fingerprinting of extremely similar mixtures over a wide range of analyte types, both in the gas and liquid phases.

An optical nose chip based on mesoporous colloidal photonic crystal beads

An optical nose chip is developed using surface functionalized mesoporous colloidal photonic crystal beads as elements. The prepared optical nose chip displays excellent discrimination among a very wide range of compounds, not only the simplex organic vapors from the different or same chemical family, but also the complex expiratory air from different people.

Hybrid integrated label-free chemical and biological sensors

Label-free sensors based on electrical, mechanical and optical transduction methods have potential applications in numerous areas of society, ranging from healthcare to environmental monitoring. Initial research in the field focused on the development and optimization of various sensor platforms fabricated from a single material system, such as fiber-based optical sensors and silicon nanowire-based electrical sensors. However, more recent research efforts have explored designing sensors fabricated from multiple materials. For example, synthetic materials and/or biomaterials can also be added to the sensor to improve its response toward analytes of interest. By leveraging the properties of the different material systems, these hybrid sensing devices can have significantly improved performance over their single-material counterparts (better sensitivity, specificity, signal to noise, and/or detection limits). This review will briefly discuss some of the methods for creating these multi-material sensor platforms and the advances enabled by this design approach.

Pen-Writing Polypyrrole Arrays on Paper for Versatile Cheap Sensors

A simple and low-cost "pen-writing" method is exploited for integrating conducting polymer on cellulosic paper. The pen-written paper chip not only possesses excellent mechanical and electrical properties, but also serves as a versatile sensor, fulfilling several real-time and in situ detections for ammonia gas, thermal heating, and NIR light. The theoretical detection limit of ammonia gas can be as low as 1.2 ppm, which is a promising performance for industrial application. In addition, this "pen-writing" technique can be extended to generate wearable electrical textiles in a large scale.