USE OF CHEMICAL SENSOR ARRAYS FOR FOOD AND FRAGRANCE ANALYSIS

Many workers have recently developed and demonstrated the use of gas sensor arrays to detect and recognize a variety of compounds. In general, a pattern recognition approach is used in which the signature of an unknown sample is compared to a library of signatures of known substances. All of these efforts have shown varying degrees of success when applied to pure compounds. Unfortunately, flavors and fragrances are never pure compounds. A prototype gas sensor array has been constructed and tested with various mixtures of interest. The results are discussed in terms of their implication to the food and fragrance industry. Early experiments on gasoline-alcohol mixtures demonstrated that the signatures do not follow a rule of mixing, but were more strongly influenced by the more volatile and/or more reactive component. This led us to examine the behavior of alcohol-water mixtures for possible quality control in the distilling industry. We discovered that the signature of alcohol dominated even at concentrations as low as ten percent. Preliminary experiments were also performed to see if the prototype sensor array could be used to automatically detect rancidity in dairy products. Flavorings and essential oils are in many cases even more complex mixtures. The behavior of representative classes of these substances were characterized in an attempt to understand their signatures on the basis of their constituents.     

Decoding complex chemical mixtures with a physical model of a sensor array

Combinatorial sensor arrays, such as the olfactory system, can detect a large number of analytes using a relatively small number of receptors. However, the complex pattern of receptor responses to even a single analyte, coupled with the non-linearity of responses to mixtures of analytes, makes quantitative prediction of compound concentrations in a mixture a challenging task. Here we develop a physical model that explicitly takes receptor-ligand interactions into account, and apply it to infer concentrations of highly related sugar nucleotides from the output of four engineered G-protein-coupled receptors. We also derive design principles that enable accurate mixture discrimination with cross-specific sensor arrays. The optimal sensor parameters exhibit relatively weak dependence on component concentrations, making a single designed array useful for analyzing a sizable range of mixtures. The maximum number of mixture components that can be successfully discriminated is twice the number of sensors in the array. Finally, antagonistic receptor responses, well-known to play an important role in natural olfactory systems, prove to be essential for the accurate prediction of component concentrations.     

Integrated Terahertz Surface Plasmon Resonance on Polyvinylidene Fluoride Layer for the Profiling of Fluid Reflectance Spectra

We design terahertz (THz) surface-plasmon-resonance (SPR) sensors using a ferroelectric polyvinylidene fluoride (PVDF) thin layer for biological sensing. The reflectivity properties based on SPR are described using transfer matrix method (TMM) and numerically simulated using finite-difference time domain (FDTD) method. The sensing characteristics of the structure are systematically analyzed through the examination of the reflectivity spectrum. The results reveal that the pronounced SPR resonance peak has quasi-linear relationship with the refractive index variation of the material under investigation. Through analyzing and optimizing the structural parameters of the THz SPR sensor, we achieved the theoretical value of the refractive index detection sensitivity as high as 0.393 THz/unit change of refractive index (RIU) for a 20-μm-thick liquid sample with a 10-μm PVDF layer. This work shows great promise toward realizing a THz SPR sensor with high sensitivity for identifying the signatures of biological fluid sample.     

A viscosity-dependent affinity sensor for continuous monitoring of glucose in biological fluids

We present a viscometric affinity biosensor for continuous monitoring of glucose in biological fluids such as blood and plasma. The sensing principle of this chemico-mechanical sensor is based upon the viscosity variation of a sensitive fluid with glucose concentration. Basically, this device includes both an actuating and a sensing piezoelectric diaphragms as well as a flow-resistive microchannel. In order to confine the sensitive fluid and allow glucose diffusion into the sensor, a free-standing alumina nanoporous membrane is also used as size-selective interface. Measurements carried out at nominal temperatures of 25 and 37 °C reveal that this sensor topology exhibits a high resolution in the current range of physiological blood glucose concentrations, i.e. 2-20 mM. In addition, complete reversibility was also demonstrated for at least 3 days. Finally, measurements performed in human blood serum confirm that this sensor fulfils all basic requirements for a use in continuous glucose monitoring of biological fluids.     

NMR of Microencapsulated Fish Oil Samples During In Vitro Digestion

The use of nuclear magnetic resonance (NMR) spectroscopy for characterising microencapsulated tuna oil powders (25% and 50% w/w oil) and assessing the behaviour of the microcapsules on their exposure to water, simulated gastric fluid or to sequential exposure of simulated gastric and intestinal fluids was examined. The matrices used for encapsulation were physical mixtures of casein or whey protein in combination with carbohydrates (dextrose monohydrate with either dried glucose syrup or a physically modified resistant starch) or heated mixtures of these matrices. Solid-state ¹³C cross-polarised magic angle spinning NMR and dipolar de-coupled magic angle spinning NMR record the ¹³C NMR signals of the encapsulant material and that of the encapsulated oil, respectively. ¹H and ¹³C solution NMR were used to investigate the relative increase in mobility of the various encapsulant matrices due to their dissolution on exposure to gastrointestinal fluids. The results suggested that the dissolution characteristics of matrices of microencapsulated oil powders were dependent on the type of milk protein and carbohydrate used and whether the protein–carbohydrate matrices were heat-treated prior to encapsulation of the oil.     

Carbon nanotube based aliphatic hydrocarbon sensor

A hybrid multi-walled carbon nanotube (MWCNT) based chemical sensor was designed and developed by integration of microfabrication techniques with nano-assembly. This integrated sensing mechanism on a chip, comprised of thiol functionalized MWCNTs that functioned as transducers which were integrated with micro-electrode array measurement sites. The detection of the four fundamental hydrocarbons belonging to the aliphatic hydrocarbon family--methanol, ethanol, propanol and butanol was experimentally demonstrated. High degree of selectivity was demonstrated by repeated robust identification of individual hydro carbons belonging to the same family. The sensor demonstrated 1 ppm detection sensitivity. The detection mechanism was based on nano-scale transduction of the detection of the localized binding event between the functional binding sites and the chemical species of interest. Specific electrical signatures for each of these chemicals were identified using multiple levels of data analysis comprising of Fast Fourier Transformation (FFT) and Power Spectral Density (PSD). The sensor demonstrated a rapid response time with portability, accuracy and versatility for the in situ detection of multiple chemical agents, with potential for automation.     

State-of-the-art two-dimensional gel electrophoresis: a key tool of proteomics research

Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) is the most popular and versatile method of protein separation among a rapidly growing array of proteomics technologies. Based on two distinct procedures, it combines isoelectric focusing (IEF), which separates proteins according to their isoelectric point (pI), and SDS-PAGE, which separates them further according to their molecular mass. At present, 2D-PAGE is capable of simultaneously detecting and quantifying up to several thousand protein spots in the same gel image. Here we provide comprehensive step-by-step instructions for the application of a standardized 2D-PAGE protocol to a sample of human plasma or cerebrospinal fluid (CSF). The method can be easily adapted to any type of sample. This four-day protocol provides detailed information on how to apply complex biological fluids to an immobilized dry strip gel, cast home-made gradient acrylamide gels, run the gels, and perform standard staining methods. A troubleshooting guide is also included.     

A signature-based method to distinguish time-of-flight secondary-ion mass spectra from biological samples

Time-Of-Flight Mass Spectrometry (TOF-SIMS) was used to determine elemental and biomolecular ions from isolated protein samples. We identified a set of 23 mass-to-charge ratio (m/z) peaks that represent signatures for distinguishing biological samples. The 23 peaks were identified by Singular Value Decomposition (SVD) and Canonical Analysis (CA) to find the underlying structure in the complex mass-spectra data sets. From this modified data, SVD was used to identify sets of m/z peaks, and we used these patterns from the TOF-SIMS data to predict the biological source from which individual mass spectra were generated. The signatures were validated using an additional data set different from the initial training set used to identify the signatures. We present a simple method to identify multiple variables required for sample classification based on mass spectra that avoids overfit. This is important in a variety of studies using mass spectrometry, including the ability to identify proteins in complex mixtures and for the identification of new biomarkers.     

Experimental and numerical estimations into the force distribution on an occlusal surface utilizing a flexible force sensor array

This study presents a novel flexible force sensor array for measuring the distribution of the force distribution over the first molar. The developed force sensor array is composed of a flexible polyimide electrode and barium-titanate-based multilayer ceramic capacitors (MLCCs). The piezoelectric and material properties of industrial-grade MLCCs are ideal for measuring large-force loadings. The sensors are cheap and easy to integrate with automated manufacturing processes. Prior to experimental measurements, the force responses for the MLCC sensor cells were systematically measured and evaluated, confirming their high fracture strength and good sensing properties. Finite element (FE) simulations were used to calculate the force distribution over the tooth crown from the measurement results of the 3×3 force sensor array. Results indicate that the sensor has great sensitivity and linearity under a high-speed cycle loading of 500 N/s conducted to simulate normal chewing. The total force measured using the developed sensor array within the artificial tooth had an error of less than 5%. In addition, the force distributions over the molar crown obtained using a numerical method of FE analysis agree well with those obtained from experiments. The developed flexible force sensor array thus has potential for in-situ bite force measurements that are low-cost and reliable.     

Fabricating optical fiber imaging sensors using ink jet printing technology: a pH sensor proof-of-concept

We demonstrate the feasibility of using Drop-on-Demand microjet printing technology for fabricating imaging sensors by reproducibly printing an array of photo-polymerizable sensing elements, containing a pH sensitive indicator, on the surface of an optical fiber image guide. The reproducibility of the microjet printing process is excellent for microdot (i.e. micrometer-sized polymer) sensor diameter (92.2+/-2.2 microm), height (35.0+/-1.0 microm), and roundness (0.00072+/-0.00023). pH sensors were evaluated in terms of pH sensing ability (< or =2% sensor variation), response time, and hysteresis using a custom fluorescence imaging system. In addition, the microjet technique has distinct advantages over other fabrication methods, which are discussed in detail.     

Calcium decoding mechanisms in plants

Ca²⁺ is a crucial second messenger that is involved in mediating responses to various biotic and abiotic environmental cues and in the regulation of many developmental processes in plants. Intracellular Ca²⁺ signals are realized by spatially and temporally defined changes in Ca²⁺ concentration that represent stimulus-specific Ca²⁺ signatures. These Ca²⁺ signatures are sensed, decoded and transmitted to downstream responses by a complex tool kit of Ca²⁺ binding proteins that function as Ca²⁺ sensors. Plants possess an extensive and complex array of such Ca²⁺ sensors that convey the information presented in the Ca²⁺ signatures into phosphorylation events, changes in protein-protein interactions or regulation of gene expression. Prominent Ca²⁺ sensors like, Calmodulins (CaM), Calmodulin-like proteins (CMLs), calcium dependent protein kinases (CDPKs), Calcineurin B-like proteins (CBLs) and their interacting kinases (CIPKs) exist in complex gene families and form intricate signaling networks in plants that are capable of robust and flexible information processing. In this review we reflect on the recently gained knowledge about the mechanistic principles of these Ca²⁺ sensors, their biochemical properties, physiological functions and newly identified targets proteins. These aspects will be discussed in the context of emerging functional principles that govern the information processing via these signaling modules.     

Developments in ecotoxicity testing

Effluent discharges from industrial facilitiesare complex, comprising of many differentcomponents and vary continuously in quantityand quality. Traditionally aquatic ecosystemshave been protected from anthropogenic impactsby controlling the input of wastewaters andother sources of pollution, which reducedissolved oxygen concentrations in receivingwaters. Recent attention has focused on thedirect effects that toxic pollutants can impacton biological systems. Consequently, the use ofwhole effluent testing has increased as arapidly and cost-effective means of evaluatingand controlling the environmental impact ofsuch emissions. However, unless the causes ofthe toxicity can be identified, the toxicity ofthe effluent cannot be effectively managed. Thetraditional way of identifying the toxicelements is to conduct a ToxicityIdentification Evaluation (TIE). However, thisprovides little information on the toxicity ofdefined mixtures of chemicals. This paperreviews the current status of aquatic toxicitytesting in relation to test species,methodology and media and compares the resultsof exposure of individual compounds to that ofchemical mixtures. It discusses the applicationof using mathematical models to predict thetoxicity of chemical mixtures in order toreduce the need to generate large amounts ofexperimental data. The different regulatoryapproaches between North America and Europe areintroduced for testing the toxicity ofdischarges to the aquatic environment as wellas the need for future research.     

Real-time odor discrimination using a bioelectronic sensor array based on the insect electroantennogram

Current trends in artificial nose research are strongly influenced by knowledge of biological olfactory systems. Insects have evolved over millions of years to detect and maneuver toward a food source or mate, or away from predators. The insect olfactory system is able to identify volatiles on a time scale that matches their ability to maneuver. Here, biological olfactory sense organs, insect antennae, have been exploited in a hybrid-device biosensor, demonstrating the ability to identify individual strands of odor in a plume passing over the sensor on a sub-second time scale. A portable system was designed to utilize the electrophysiological responses recorded from a sensor array composed of male or female antennae from four or eight different species of insects (a multi-channel electroantennogram, EAG). A computational analysis strategy that allows discrimination between odors in real time is described in detail. Following a training period, both semi-parametric and k-nearest neighbor (k-NN) classifiers with the ability to discard ambiguous responses are applied toward the classification of up to eight odors. EAG responses to individual strands in an odor plume are classified or discarded as ambiguous with a delay (sensor response to classification report) on the order of 1 s. The dependence of classification error rate on several parameters is described. Finally, the performance of the approach is compared to that of a minimal conditional risk classifier.     

Acoustic recognition in macaroni penguins: an original signature system

Penguins use vocal signatures as cues to identify their kin in dense colonies. Experimental studies of four species in two genera have pointed out that vocal signatures depend on the breeding ecology of the birds. Penguins that have a meeting site for pair members and chicks (genus Pygoscelis), as in many seabirds, have a less complex vocal signature than penguins that have no nests (genus Aptenodytes). To investigate whether this pattern would extend to other nest-building penguins, we studied the vocal signature in a species of the genus Eudyptes, the macaroni penguin, E. chrysolophus. Temporal and spectral features of signatures were analysed to determine which were likely to encode individual identity. Using a methodology derived from the theory of information, we measured and compared the amount of information given by each of these parameters by means of a stereotypy index. We then tested their effective efficiency in playback experiments of modified calls. Like Aptenodytes species, the macaroni penguins used a double coding system that integrated information in both the temporal and spectral domains. The encoding was made through the tempo given by the successive syllables of the call and the harmonic content of the call. However, information was not complementary but was mostly repeated in both domains, and variables were unidimensional as in Pygoscelis signatures. These results point out an original and simple signature system in macaroni penguins. Although they support the hypothesis of simpler systems in nest-building species they also reveal more subtle differences within this category.     

Autofluorescence excitation‐emission matrices as a quantitative tool for the assessment of meat quality

Commercially produced meat is currently graded by a complex and partly subjective multiparameter methodology; a quantitative method of grading, using small samples would be desirable. Here, we investigate the correlation between commercial grades of beef and spectral signatures of native fluorophores in such small samples. Beef samples of different commercial grades were characterized by fluorescence spectroscopy complemented by biochemical and histological assessment. The excitation‐emission matrices of the specimens reveal five prominent native autofluorescence signatures in the excitation range from 250 to 350 nm, derived mainly from tryptophan and intramuscular fat. We found that these signatures reflect meat grade and can be used for its determination.      

Active touch sensing

Active sensing systems are purposive and information-seeking sensory systems. Active sensing usually entails sensor movement, but more fundamentally, it involves control of the sensor apparatus, in whatever manner best suits the task, so as to maximize information gain. In animals, active sensing is perhaps most evident in the modality of touch. In this theme issue, we look at active touch across a broad range of species from insects, terrestrial and marine mammals, through to humans. In addition to analysing natural touch, we also consider how engineering is beginning to exploit physical analogues of these biological systems so as to endow robots with rich tactile sensing capabilities. The different contributions show not only the varieties of active touch--antennae, whiskers and fingertips--but also their commonalities. They explore how active touch sensing has evolved in different animal lineages, how it serves to provide rapid and reliable cues for controlling ongoing behaviour, and even how it can disintegrate when our brains begin to fail. They demonstrate that research on active touch offers a means both to understand this essential and primary sensory modality, and to investigate how animals, including man, combine movement with sensing so as to make sense of, and act effectively in, the world.     

Numerical simulations of odorant detection by biologically inspired sensor arrays

The antennules of many marine crustaceans enable them to rapidly locate sources of odorant in turbulent environmental flows and may provide biological inspiration for engineered plume sampling systems. A substantial gap in knowledge concerns how the physical interaction between a sensing device and the chemical filaments forming a turbulent plume affects odorant detection and filters the information content of the plume. We modeled biological arrays of chemosensory hairs as infinite arrays of odorant flux-detecting cylinders and simulated the fluid flow around and odorant flux into the hair-like sensors as they intercepted a single odorant filament. As array geometry and sampling kinematics were varied, we quantified distortion of the flux time series relative to the spatial shape of the original odorant filament as well as flux metrics that may be important to both organisms and engineered systems attempting to measure plume structure and/or identify chemical composition. The most important predictor of signal distortion is the ratio of sensor diameter to odorant filament width. Achieving high peak properties (e.g. sharpness) of the flux time series and maximizing the total number of odorant molecules detected appear to be mutually exclusive design goals. Sensor arrays inspired specifically by the spiny lobster Panulirus argus and mantis shrimp Gonodactylaceus falcatus introduce little signal distortion but these species' neural systems may not be able to resolve plume structure at the level of individual filaments via temporal properties of the odorant flux. Current chemical sensors are similarly constrained. Our results suggest either that the spatial distribution of flux across the aesthetasc array is utilized by P. argus and G. falcatus, or that such high spatiotemporal resolution is unnecessary for effective plume tracking.     

Mesoporous silica chips for selective enrichment and stabilization of low molecular weight proteome

The advanced properties of mesoporous silica have been demonstrated in applications, which include chemical sensing, filtration, catalysis, drug delivery and selective biomolecular uptake. These properties depend on the architectural, physical and chemical properties of the material, which in turn are determined by the processing parameters in evaporation‐induced self‐assembly. In this study, we introduce a combinatorial approach for the removal of the high molecular weight proteins and for the specific isolation and enrichment of low molecular weight species. This approach is based on mesoporous silica chips able to fractionate, selectively harvest and protect from enzymatic degradation, peptides and proteins present in complex human biological fluids. We present the characterization of the harvesting properties of a wide range of mesoporous chips using a library of peptides and proteins standard and their selectivity on the recovery of serum peptidome. Using MALDI‐TOF‐MS, we established the correlation between the harvesting specificity and the physicochemical properties of mesoporous silica surfaces. The introduction of this mesoporous material with fine controlled properties will provide a powerful platform for proteomics application offering a rapid and efficient methodology for low molecular weight biomarker discovery.