Colorimetric Sensor Arrays for Volatile Organic Compounds

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.

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.

Differentiation among peroxide explosives with an optoelectronic nose

Forensic identification of batches of homemade explosives (HME) poses a difficult analytical challenge. Differentiation among peroxide explosives is reported herein using a colorimetric sensor array and handheld scanner with a field-appropriate sampling protocol. Clear discrimination was demonstrated among twelve peroxide samples prepared from different reagents, with a classification accuracy >98%.

Advances in the early detection of lung cancer using analysis of volatile organic compounds: from imaging to sensors

According to the World Health Organization (WHO), 1.37 million people died of lung cancer all around the world in 2008, occupying the first place in all cancer-related deaths. However, this number might be decreased if patients were detected earlier and treated appropriately. Unfortunately, traditional imaging techniques are not sufficiently satisfactory for early detection of lung cancer because of limitations. As one alternative, breath volatile organic compounds (VOCs) may reflect the biochemical status of the body and provide clues to some diseases including lung cancer at early stage. Early detection of lung cancer based on breath analysis is becoming more and more valued because it is non-invasive, sensitive, inexpensive and simple. In this review article, we analyze the limitations of traditional imaging techniques in the early detection of lung cancer, illustrate possible mechanisms of the production of VOCs in cancerous cells, present evidence that supports the detection of such disease using breath analysis, and summarize the advances in the study of E-noses based on gas sensitive sensors. In conclusion, the analysis of breath VOCs is a better choice for the early detection of lung cancer compared to imaging techniques. We recommend a more comprehensive technique that integrates the analysis of VOCs and non-VOCs in breath. In addition, VOCs in urine may also be a trend in research on the early detection of lung cancer.

The development of a disposable gas chromatography microcolumn

The first molded-polymer gas chromatography (GC) microcolumn (made of a phase-separated, microtextured thermoset polymer) is described and characterized.

Dye immobilization in halochromic nanofibers through blend electrospinning of a dye-containing copolymer and polyamide-6

Halochromic polyamide6-based fabrics with drastically reduced dye-leaching through blend electrospinning of PA6 with dye-functionalized copolymer.

Solvatochromic sensor array for the identification of common organic solvents

A solvatochromic colorimetric sensor array was used to discriminate among common solvents; chemical and physical changes contribute to array response.

Protein recognition using synthetic small-molecular binders toward optical protein sensing in vitro and in live cells

This review describes the recognition and sensing techniques of proteins and their building blocks by use of small synthetic binders.

Distyrylbenzene-aldehydes: identification of proteins in water

Herein we describe the discrimination of different albumins using fluorescence changes in a simple three-compound array and apply this system in the differentiation of protein shake powders.

Development of a colorimetric sensor array for the discrimination of Chinese liquors based on selected volatile markers determined by GC-MS

A new colorimetric sensor array was developed for the discrimination of 12 high-alcoholic Chinese base liquors from Luzhou Co., Ltd., and 15 commercial Chinese liquor of different brands as well as flavor types. Seventeen volatile compounds within four chemical groups were determined as markers in the base liquor by GC-MS analysis and factor analysis method (FAM). A specialized colorimetric sensor array composed of 20 sensitive dots was fabricated accordingly to obtain sensitive interaction with different types of volatile markers. Discrimination of the liquor samples was subsequently performed using chemometric and statistical methods, including principal component analysis (PCA) and hierarchical clustering analysis (HCA). The results suggested that facile identification of either base liquors with high-alcoholic volume or commercial liquors of the same flavor types could be achieved by analysis of the color change profiles. The response of the sensor improved significantly in comparison with those that rely on nonspecific interactions, and no misclassification was observed for both liquor samples using two chemometric methods. Besides, it was also found that the discrimination is closely related to the characteristic flavor compounds (esters, aldehydes, and acids) and alcoholic strength in liquors, and its performance was even comparable with that of GC-MS.

A novel electronic nose based on porous In2O3 microtubes sensor array for the discrimination of VOCs

We have innovatively developed an electronic nose consisting of only one type of semiconductor metal oxide (SMO) material. The representative SMO material, porous In2O3 microtubes in this work, offered great surface area and large gas penetration channels. By using a solvent casting process, different amounts of porous In2O3 microtubes were coated on Al2O3 substrate, forming a resistometric SMO sensor array-based electronic nose. Each sensing unit in the electronic nose exhibited independent response toward ethanol. We have successfully applied this electronic nose to distinguish four alcohols at the same concentrations (100 ppm), and also utilized the electronic nose for the discrimination of 14 volatile organic compounds (VOCs). Clear differentiation among all the 14 VOCs both at their immediately dangerous to life or health (IDLH) and the permissible exposure limit (PEL) concentrations has been achieved with no errors or misclassifications. We expect that this method will expand the application of SMO sensor array-based electronic nose which has been largely limited by the selection of commercially available SMOs and dopants.

Biomedical imaging and sensing using flatbed scanners

In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600-700 cm(2)) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings.

Hybrid mesoporous colloid photonic crystal array for high performance vapor sensing

A hybrid mesoporous photonic crystal vapor sensing chip was developed by introducing fluorescent dyes into mesoporous colloidal crystals. The sensing chip was capable of discriminating various kinds of vapors, as well as their concentrations, according to their fluorescence and reflective responses to vapor analytes.

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.

Identification of pathogenic fungi with an optoelectronic nose

Human fungal infections have gained recent notoriety following contamination of pharmaceuticals in the compounding process. Such invasive infections are a more serious global problem, especially for immunocompromised patients. While superficial fungal infections are common and generally curable, invasive fungal infections are often life-threatening and much harder to diagnose and treat. Despite the increasing awareness of the situation's severity, currently available fungal diagnostic methods cannot always meet diagnostic needs, especially for invasive fungal infections. Volatile organic compounds produced by fungi provide an alternative diagnostic approach for identification of fungal strains. We report here an optoelectronic nose based on a disposable colorimetric sensor array capable of rapid differentiation and identification of pathogenic fungi based on their metabolic profiles of emitted volatiles. The sensor arrays were tested with 12 human pathogenic fungal strains grown on standard agar medium. Array responses were monitored with an ordinary flatbed scanner. All fungal strains gave unique composite responses within 3 hours and were correctly clustered using hierarchical cluster analysis. A standard jackknifed linear discriminant analysis gave a classification accuracy of 94% for 155 trials. Tensor discriminant analysis, which takes better advantage of the high dimensionality of the sensor array data, gave a classification accuracy of 98.1%. The sensor array is also able to observe metabolic changes in growth patterns upon the addition of fungicides, and this provides a facile screening tool for determining fungicide efficacy for various fungal strains in real time.

Dosimetric characteristics of a radiochromic polyvinyl butyral film containing 2,4-hexadiyn-1,6-bis(n-butyl urethane)

A radiation-sensitive compound 2,4-hexadiyn-1,6-bis(n-butyl urethane) (HDDBU) was synthesized, characterized by FTIR spectroscopy, and introduced into a thin polyvinyl butyral film to form a radiation dosimeter for industrial irradiation facilities. The monomer polymerizes under gamma radiation, inducing change in the film spectrum in the range of 200-400 nm. According to XRD spectroscopy, the film contains monomeric HDDBU in a non-crystalline state. The dose response function, radiation sensitivity, and dependences of the response on environmental factors were studied. Uncertainty of dose measurements with the proposed dosimetry system was analyzed in detail.

Reactive Arrays of Colorimetric Sensors for Metabolite and Steroid Identification

The work described herein examines a rapid mix-and-measure method called DETECHIP suitable for screening of steroids and metabolites. The addition of steroids and metabolites to reactive arrays of colorimetric sensors generated characteristic color “fingerprints” that were used to identify the analyte. A color analysis tool was used to identify the analyte pool that now includes biologically relevant analytes. The mix-and-measure arrays allowed the detection of disease metabolites, orotic acid and argininosuccinic acid; and the steroids androsterone, 1,4-androstadiene, testosterone, stanozolol, and estrone. The steroid 1,4-androstadiene was also detected by this method while dissolved in synthetic urine. Some of the steroids, such as androstadiene, stanozolol, and androsterone were co-dissolved with (2-hydroxypropyl)-β-cyclodextrin in order to increase solubility in aqueous buffered solutions. The colorimetric arrays do not intend to eliminate ELISA or mass spectroscopy based screening, but to possibly provide an alternative analytical detection method for steroids and metabolites.

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.

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.

Giga-pixel fluorescent imaging over an ultra-large field-of-view using a flatbed scanner

We demonstrate a new fluorescent imaging technique that can screen for fluorescent micro-objects over an ultra-wide field-of-view (FOV) of ~532 cm(2), i.e., 19 cm × 28 cm, reaching a space-bandwidth product of more than 2 billion. For achieving such a large FOV, we modified the hardware and software of a commercially available flatbed scanner, and added a custom-designed absorbing fluorescent filter, a two-dimensional array of external light sources for computer-controlled and high-angle fluorescent excitation. We also re-programmed the driver of the scanner to take full control of the scanner hardware and achieve the highest possible exposure time, gain and sensitivity for detection of fluorescent micro-objects through the gradient index self-focusing lens array that is positioned in front of the scanner sensor chip. For example, this large FOV of our imaging platform allows us to screen more than 2.2 mL of undiluted whole blood for detection of fluorescent micro-objects within <5 minutes. This high-throughput fluorescent imaging platform could be useful for rare cell research and cytometry applications by enabling rapid screening of large volumes of optically dense media. Our results constitute the first time that a flatbed scanner has been converted to a fluorescent imaging system, achieving a record large FOV.

Computational imaging, sensing and diagnostics for global health applications

In this review, we summarize some of the recent work in emerging computational imaging, sensing and diagnostics techniques, along with some of the complementary non-computational modalities that can potentially transform the delivery of health care globally. As computational resources are becoming more and more powerful, while also getting cheaper and more widely available, traditional imaging, sensing and diagnostic tools will continue to experience a revolution through simplification of their designs, making them compact, light-weight, cost-effective, and yet quite powerful in terms of their performance when compared to their bench-top counterparts.

The use of principal component analysis and discriminant analysis in differential sensing routines

Statistical analysis techniques such as principal component analysis (PCA) and discriminant analysis (DA) have become an integral part of data analysis for differential sensing. These multivariate statistical tools, while extremely versatile and useful, are sometimes used as "black boxes". Our aim in this paper is to improve the general understanding of how PCA and DA process and display differential sensing data, which should lead to the ability to better interpret the final results. With various sets of model data, we explore several topics, such as how to choose an appropriate number of hosts for an array, selectivity compared to cross-reactivity, when to add hosts, how to obtain the best visually representative plot of a data set, and when arrays are not necessary. We also include items at the end of the paper as general recommendations which readers can follow when using PCA or DA in a practical application. Through this paper we hope to present these statistical analysis methods in a manner such that chemists gain further insight into approaches that optimize the discriminatory power of their arrays.

DNA-polyfluorophore Chemosensors for Environmental Remediation: Vapor-phase Identification of Petroleum Products in Contaminated Soil

Contamination of soil and groundwater by petroleum-based products is an extremely widespread and important environmental problem. Here we have tested a simple optical approach for detecting and identifying such industrial contaminants in soil samples, using a set of fluorescent DNA-based chemosensors in pattern-based sensing. We used a set of diverse industrial volatile chemicals to screen and identify a set of five short oligomeric DNA fluorophores on PEG-polystyrene microbeads that could differentiate the entire set after exposure to their vapors in air. We then tested this set of five fluorescent chemosensor compounds for their ability to respond with fluorescence changes when exposed to headgas over soil samples contaminated with one of ten different samples of crude oil, petroleum distillates, fuels, lubricants and additives. Statistical analysis of the quantitative fluorescence change data (as Δ(R,G,B) emission intensities) revealed that these five chemosensors on beads could differentiate all ten product mixtures at 1000 ppm in soil within 30 minutes. Tests of sensitivity with three of the contaminant mixtures showed that they could be detected and differentiated in amounts at least as low as one part per million in soil. The results establish that DNA-polyfluorophores may have practical utility in monitoring the extent and identity of environmental spills and leaks, while they occur and during their remediation.

Smelling in chemically complex environments: an optofluidic Bragg fiber array for differentiation of methanol adulterated beverages

A novel optoelectronic nose for analysis of alcohols (ethanol and methanol) in chemically complex environments is reported. The cross-responsive sensing unit of the optoelectronic nose is an array of three distinct hollow-core infrared transmitting photonic band gap fibers, which transmit a specific band of IR light depending on their Bragg mirror structures. The presence of alcohol molecules in the optofluidic core quenches the fiber transmissions if there is an absorption band of the analyte overlapping with the transmission band of the fiber; otherwise they remain unchanged. The cumulative response data of the fiber array enables rapid, reversible, and accurate discrimination of alcohols in chemically complex backgrounds such as beer and fruit juice. In addition, we observed that humidity of the environment has no effect on the response matrix of the optoelectronic nose, which is rarely achieved in gas-sensing applications. Consequently, it can be reliably used in virtually any environment without precalibration for humidity or drying the analytes. Besides the discussed application in counterfeit alcoholic beverages, with its superior sensor parameters, this novel concept proves to be a promising contender for many other applications including food quality control, environmental monitoring, and breath analysis for disease diagnostics.

Classification of tea category using a portable electronic nose based on an odor imaging sensor array

A developed portable electronic nose (E-nose) based on an odor imaging sensor array was successfully used for classification of three different fermentation degrees of tea (i.e., green tea, black tea, and Oolong tea). The odor imaging sensor array was fabricated by printing nine dyes, including porphyrin and metalloporphyrins, on the hydrophobic porous membrane. A color change profile for each sample was obtained by differentiating the image of sensor array before and after exposure to tea's volatile organic compounds (VOCs). Multivariate analysis was used for the classification of tea categories, and linear discriminant analysis (LDA) achieved 100% classification rate by leave-one-out cross-validation (LOOCV). This study demonstrates that the E-nose based on odor imaging sensor array has a high potential in the classification of tea category according to different fermentation degrees.

The use of colorimetric sensor arrays to discriminate between pathogenic bacteria

A colorimetric sensor array is a high-dimensional chemical sensor that is cheap, compact, disposable, robust, and easy to operate, making it a good candidate technology to detect pathogenic bacteria, especially potential bioterrorism agents like Yersinia pestis and Bacillus anthracis which feature on the Center for Disease Control and Prevention's list of potential biothreats. Here, a colorimetric sensor array was used to continuously monitor the volatile metabolites released by bacteria in solid media culture in an Advisory Committee on Dangerous Pathogen Containment Level 3 laboratory. At inoculum concentrations as low as 8 colony-forming units per plate, 4 different bacterial species were identified with 100% accuracy using logistic regression to classify the kinetic profile of sensor responses to culture headspace gas. The sensor array was able to further discriminate between different strains of the same species, including 5 strains of Yersinia pestis and Bacillus anthracis. These preliminary results suggest that disposable colorimetric sensor arrays can be an effective, low-cost tool to identify pathogenic bacteria.

Detecting Concentration of Analytes with DETECHIP: A Molecular Sensing Array

DETECHIP^® is a detection system made of various sensors that has been shown to detect and discriminate between small molecules of interest, including various illicit and over-the-counter drugs. Previously, detection was normalized to a single concentration of analyte. Now this detection assay can detect concentration differences in analytes via red, green, and blue color value changes and shifts in the UV-Vis spectra of the assay. To determine the concentrations differences, the exposed assays were scanned on a flatbed scanner and the images were analyzed for individual RGB values with a custom macro in ImageJ, an image analysis program. Increasing concentrations of the analyte resulted in greater differences in color values between control and analyte wells. These differences showed a linear relationship to concentration change, some with correlation coefficients greater than 98%. This work expands the capability of DETECHIP to give information about the concentration of analyte when the analyte identity is known.

An excellent copper selective chemosensor based on calix[4]arene framework

The article depicts a detailed study regarding copper selective chemosensing and complexation nature of 5,11,17,23-tetrakis[(N,N-diphenylamino)methyl]-25,26,27,28-tetrahydroxycalix[4]arene (PAC4). Its photophysical characteristics in various solvents of different polarities along with the influence of acid and base on its spectral properties in these solvents are also discussed. The complexation affinity of PAC4 with regard to its latent applications as Cu(II) selective colorimetric and fluorescent sensor among the selected series of various cations such as Li(I), Na(I), K(I), Rb(I), Ba(II), Sr(II), Al(III), Fe(III), Cd(II), Co(II), Hg(II), Mn(II), Ni(II), Pb(II) and Zn(II) was examined by UV-visible and fluorescence emission spectroscopy in dichloromethane:acetonitrile (DCM:MeCN) solvent system. In addition, the process of complexation has been investigated through Job's plot and it has been observed that the complex between PAC4 and Cu(II) is formed in 1:1 stoichiometric ratio. The complex formation between PAC4 and Cu(II) has also been confirmed by FT-IR spectroscopy and thermal gravimetric analysis (TGA).