Nano‐Graphene Oxide Based Multichannel Sensor Arrays towards Sensing of Protein Mixtures

Optical array‐based sensors are attractive candidates for the detection of various bio‐analytes due to their convenient fabrication and measurements. For array‐based sensors, multichannel arrays are more advantageous and used frequently in many electronic sensors. But most reported optically array based sensors are constructed on a single channel array. This difficulty is mainly instigated from the overlap in optical responses. In this report we have used nano‐graphene oxide (nGO) and suitable fluorophores as sensor elements to construct a multichannel sensor array for the detection of protein analytes. By using the optimized multichannel array we are able to detect different proteins and mixtures of proteins with 100 % classification accuracy at sub‐nanomolar concentration. This modified method expedites the sensing analysis as well as minimizes the use of both analyte and sensor elements in array‐based protein sensing. We have also used this system for the single channel array‐based sensing to compare the sensitivity and the efficacy of these two systems for other applications. This work demonstrated an intrinsic trade‐off associated with these two methods which may be necessary to balance for array‐based analyte detections.     

Chemical vapor discrimination using a compact and low-power array of piezoresistive microcantilevers

A compact and low-power microcantilever-based sensor array has been developed and used to detect various chemical vapor analytes. In contrast to earlier micro-electro-mechanical systems (MEMS) array sensors, this device uses the static deflection of piezoresistive cantilevers due to the swelling of glassy polyolefin coatings during sorption of chemical vapors. To maximize the sensor response to a variety of chemical analytes, the polymers are selected based on their Hildebrand solubility parameters to span a wide range of chemical properties. We utilize a novel microcontact spotting method to reproducibly coat a single side of each cantilever in the array with the polymers. To demonstrate the utility of the sensor array we have reproducibly detected 11 chemical vapors, representing a breadth of chemical properties, in real time and over a wide range of vapor concentrations. We also report the detection of the chemical warfare agents (CWAs) VX and sulfur mustard (HD), representing the first published report of CWA vapor detection by a polymer-based, cantilever sensor array. Comparisons of the theoretical polymer/vapor partition coefficient to the experimental cantilever deflection responses show that, while general trends can be reasonably predicted, a simple linear relationship does not exist.     

VOCs分子的半导体型传感器识别检测研究进展

具有体积小、功耗低、灵敏度高、硅工艺兼容性好等优点的金属氧化物半导体(MOS)气体传感器现已广泛地应用于军事、科研和国民经济的各个领域。然而MOS传感器的低选择性阻碍了其在物联网(IoT)时代的应用前景。为此,本文综述了解决MOS传感器选择性的研究进展,主要介绍了敏感材料性能提升、电子鼻和热调制三种改善MOS传感器选择性的技术方法,阐述了三种方法目前所存在的问题及其未来的发展趋势。同时,本文还对比介绍了机器嗅觉领域主流的主成分分析(PCA)、线性判别分析(LDA)和神经网络(NN)模式识别/机器学习算法。最后,本综述展望了具有数据降维、特征提取和鲁棒性识别分类性能的卷积神经网络(CNN)深度学习算法在气体识别领域的应用前景。基于敏感材料性能的提升、多种调制手段与阵列技术的结合以及人工智能(AI)领域深度学习算法的最新进展,将会极大地增强非选择性MOS传感器的挥发性有机化合物(VOCs)分子识别能力。     

Structural variability of nucleosomes detected by single-pair Förster resonance energy transfer: histone acetylation, sequence variation, and salt effects

Nucleosomes were reconstituted from 170 bp long fragments of 5S rDNA and an optimal positioning sequence, the Selex 601, with recombinant histones. In free-solution single pair F?rster resonance energy transfer (spFRET) measurements of the distance between fluorescently labeled bases in the nucleosomal DNA, the samples exhibited structural diversity. The structural heterogeneity correlated with the stability of the complexes and depended on the DNA sequence and histone acetylation. The stability of the nucleosomes was assessed via dilution-driven disruption: histone acetylation decreased nucleosome stability. The spFRET experiments used a new approach for data acquisition and analysis that we term "deliberately detuned detection" (D3). This permits the separation of subpopulations in the samples even for the low-FRET regime characteristic for the linker-DNA labeled nucleosomes. Thus, it became possible to study in more detail histone acetylation- and salt-dependent structural variations using either end- or internally labeled DNAs on the nucleosome. We found that the distance distribution of the fluorophore pairs on the linker DNA ends was much more sensitive to histone acetylation or sequence variation than that of labels on the internal part of the DNA, which was more tightly associated with the histone core. spFRET on freely diffusing nucleosomes allows us therefore to localize the influence of histone modifications and DNA sequence variations on the nucleosome structure and dynamics.     

Gas sensor array based on metal-decorated carbon nanotubes

Here we demonstrate design, fabrication, and testing of electronic sensor array based on single-walled carbon nanotubes (SWNTs). Multiple sensor elements consisting of isolated networks of SWNTs were integrated into Si chips by chemical vapor deposition (CVD) and photolithography processes. For chemical selectivity, SWNTs were decorated with metal nanoparticles. The differences in catalytic activity of 18 catalytic metals for detection of H(2), CH(4), CO, and H(2)S gases were observed. Furthermore, a sensor array was fabricated by site-selective electroplating of Pd, Pt, Rh, and Au metals on isolated SWNT networks located on a single chip. The resulting electronic sensor array, which was comprised of several functional SWNT network sensors, was exposed to a randomized series of toxic/combustible gases. Electronic responses of all sensor elements were recorded and the sensor array data was analyzed using pattern-recognition analysis tools. Applications of these small-size, low-power, electronic sensor arrays are in the detection and identification of toxic/combustible gases for personal safety and air pollution monitoring.     

Selection of a piezoelectric sensor array for detecting volatile organic substances in water

Sensitive coatings for piezoelectric sensors used to assess the presence of anthropogenic volatile organic substances in the equilibrium gas phase over natural water have been selected using an array of measuring elements, and the data have been processed using principal component analysis. Groups of piezoelectric sensors with similar characteristics for substance identification have been determined based on the correlation between piezoelectric sensor responses when vapors of organic substances were detected. The stepby-step optimization of the piezoelectric sensor array has been carried out in order to identify the greatest number of organic compounds (vapors) in the sample. Volatile organic compounds can be identified in their aqueous solutions and natural water using the optimized piezoelectric sensor array.     

Integrated chemical sensor array platform based on a light emitting diode, xerogel-derived sensor elements, and high-speed pin printing

We report a new, solid-state, integrated optical array sensor platform. By using pin printing technology in concert with sol-gel-processing methods, we form discrete xerogel-based microsensor elements that are on the order of 100 μm in diameter and 1 μm thick directly on the face of a light emitting diode (LED). The LED serves as the light source to excite chemically responsive luminophores sequestered within the doped xerogel microsensors and the analyte-dependent emission from within the doped xerogel is detected with a charge coupled device (CCD). We overcome the problem of background illumination from the LED reaching the CCD and the associated biasing that results by coating the LED first with a thin layer of blue paint. The thin paint layer serves as an optical filter, knocking out the LEDs red-edge spectral tail. The problem of the spatially-dependent fluence across the LED face is solved entirely by performing ratiometric measurements. We illustrate the performance of the new sensor scheme by forming an array of 100 discrete O₂-responsive sensing elements on the face of a single LED. The combination of pin printing with an integrated sensor and light source platform results in a rapid method of forming (∼1 s per sensor element) reusable sensor arrays. The entire sensor array can be calibrated using just one sensor element. Array-to-array reproducibly is <8%. Arrays can be formed using single or multiple pins with indistinguishable analytical performance.     

Replication of DNA microarrays from zip code masters

This report describes a mechanical method for efficient and accurate replication of DNA microarrays from a zip code master. The zip code master is a DNA array that defines the location of oligonucleotides consisting of two parts: a code sequence, which is complementary to one or more of the zip codes, and the functional sequence, which is terminated with biotin. Following hybridization of the zip code to the code sequence, a replica surface functionalized with streptavidin is brought into conformal contact with the surface of the master. When the two surfaces are separated, the functional and code sequences are transferred to the replica, and the zip code remains on the surface of the master. Using this approach it is possible to prepare replica arrays having any configuration from a single, universal master array. Here we demonstrate that this approach can be used to replicate master arrays having up to three different sequences, that feature sizes as small as 100 microm can be replicated, and that master arrays can be used to prepare multiple replicas.     

Automatic decoding of sensor types within randomly ordered,high-density optical sensor arrays

In this paper automatic sensor identification of sensor classes within a high-density randomized array, without a priori knowledge of sensor locations, is demonstrated. Two different fluorescence-based sensor types, with hundreds of replicates each, were randomly distributed into an optical imaging fiber array platform. The sensor element types were vapor-sensitive microspheres with the environmentally-sensitive fluorescent dye Nile Red adsorbed on their surface. Nile Red undergoes spectral changes when exposed to different microenvironmental polarity conditions, e.g. microsphere surface polarity or odor exposure. These reproducible sensor spectral changes, or sensor-response profiles, enable sensors within a randomized array to be grouped into categories by optical decoding methods. Two computational decoding methods (supervised and unsupervised) are introduced; equal classification rates were achieved for both. By comparing sensor responses from a randomized array with those obtained from known (control) arrays, 587 sensors were correctly classified with 99.32% accuracy. Although both methods were equally effective, the unsupervised method, which uses sensor response changes to odor exposure, is a better decoding model for the vapor-sensitive arrays studied, because it relies only on the odor-response profiles. Another decoding technique employed the emission spectra of the sensors and is more applicable to other types of multiplexed fluorescence-based arrays and assays. The sensor-decoding techniques are compared to demonstrate that sensors within high-density optical chemosensor arrays can be positionally-registered, or decoded, with no additional overhead in time or expense other than collecting the sensor-response profiles.     

Optimizing cross-reactivity with evolutionary search for sensors

We report a straightforward evolutionary procedure to build an optimal sensor array from a pool of DNA sequences oriented toward three-way junctions. The individual sensors were mined from this pool under separate selection pressures to interact with four steroids, while allowing cross-reactivity, in a manner designed to achieve perfect classification of individual steroids. The resulting sensor array had three sensors and displayed discriminatory capacity between steroid classes over full ranges of concentrations. We propose that similar protocols can be used whenever we have two or more classes of samples, with individual classes being defined through gross differences in ratios of dominant families of responsive components.     

Multiplex Identification of Post-Translational Modifications at Point-of-Care by Deep Learning-Assisted Hydrogel Sensors

Multiplex detection of protein post-translational modifications (PTMs), especially at point-of-care, is of great significance in cancer diagnosis. Herein, we report a machine learning-assisted photonic crystal hydrogel (PCH) sensor for multiplex detection of PTMs. With closely-related PCH sensors microfabricated on a single chip, our design achieved not only rapid screening of PTMs at specific protein sites by using only naked eyes/cellphone, but also the feasibility of real-time monitoring of phosphorylation reactions. By taking advantage of multiplex sensor chips and a neural network algorithm, accurate prediction of PTMs by both their types and concentrations was enabled. This approach was ultimately used to detect and differentiate up/down regulation of different phosphorylation sites within the same protein in live mammalian cells. Our developed method thus holds potential for POC identification of various PTMs in early-stage diagnosis of protein-related diseases.     

Characterization of neurohistone variants and post-translational modifications by electron capture dissociation mass spectrometry

Post-translational modifications (PTMs) of histones are intimately involved in chromatin structure and thus have roles in cellular processes through their impact on gene activation or repression. At the forefront in histone PTM analysis are mass spectrometry-based techniques, which have capabilities to produce improved views of processes affected by chromatin remodeling via histone modifications. In this report, we take the first mass spectrometric look at histone variant expression and post-translational modifications from histones isolated from rat brain tissue. Analyses of whole rat brain identified specific histone H2A and H2B gene family members and several H4 and H3 post-translational modification sites by electron capture dissociation (ECD) mass spectrometry. We subsequently compared these results to selected rat brain regions. Major differences in the expression profiles of H2A and H2B gene family members or in the post-translational modifications on histone H4 were not observed from the different brain regions using a Top Down approach. However, “Middle Down” mass spectrometry facilitating improved characterization of the histone H3 tail (1–50 residues), revealed an enrichment of trimethylation on Lys9 from cerebellum tissue compared to H3 extracted from whole brain, cerebral cortex or hypothalamus tissue. We forward this study in honor of Professor Donald F. Hunt, whose pioneering efforts in protein and PTM analyses have spawned new eras and numerous careers, many exemplified in this special issue.     

Multisensor system on the basis of an array of non-specific chemical sensors and artificial neural networks for determination of inorganic pollutants in a model groundwater

The application of a multisensor system to groundwater monitoring is investigated. The sensor system is based on an array of non-specific potentiometric chemical sensors with data processing by artificial neural networks and includes 13 sensors with PVC membranes and 12 solid-state ones. Results of measurements in model solutions containing heavy metals, alkali- and alkali-earth cations and inorganic anions at concentrations typical for groundwater near the city of Braunschweig, Germany, are presented. Both the response of the whole sensor array and the responses of subsystems consisting only of PVC and only of solid-state sensors, respectively, are investigated. It is shown that both subsystems can be used for determination of described ions and that the best results are obtained if the whole array of sensors is used.     

A perfume odour-sensing system using an array of piezoelectric crystal sensors with plasticized PVC coatings

Using PVC polymer as membrane matrix and di-n-octylphenyl phosphate (DOPP) as plasticizer, a piezoelectric crystal sensor (PCS) array with 12 adsorptive materials selected from 68 compounds by cluster analysis has been constructed as a perfume odour-sensing system. The frequency shift data obtained from the sensor array responding to four commercial perfume odours are first autoscaled and then treated by principal component analysis. The experimental results show that the plasticized PVC membrane PCS array provides improved performance of pattern recognition compared with the single adsorptive coating PCS array. The frequency shift response characteristics of these sensors have been investigated experimentally. The proposed sensor array has also been applied to the classification of commercial spirituous liquor, wine and soft drink samples, as well as aliphatic alcohol homologues and isomers.     

Method of gas mixtures discrimination based on sensor array, temporal response and data driven approach

This work presents a method of gas mixtures discrimination. The principal concept of the method is to apply measurement data provided by a combination of sensors at single time point of their temporal response as input of the discrimination models. The pattern data combinations are selected for classes of target gases based on the criterion of 100% efficient discrimination. Combinations of sensors and time points, which provide pattern data combinations in course or repeated measurements, are encoded in the form of addresses. The designer of sensor system is responsible for their selection and they are included in the software of the final instrument. The study of the method involved the discrimination of gas mixtures composed of air and single chemical: hexane, ethanol, acetone, ethyl acetate and toluene. Two sensor arrays were utilized. Each consisted of six TGS sensors of the same type. The dynamic operation of sensors was employed. As an example the stop-flow mode was chosen. The work provides the evidence of the existence of sensor combinations and time points, which are successful in discrimination of studied classes of target gases. The persistence of addresses was discussed considering the ability of sensor array to recognize analytes, variability of repeated measurement results, number of repeated measurements and a twin sets of sensors. Altogether, the validity of the method was demonstrated.     

A perfume odour-sensing system using an array of piezoelectric crystal sensors with plasticized PVC coatings

Using PVC polymer as membrane matrix and di-n-octylphenyl phosphate (DOPP) as plasticizer, a piezoelectric crystal sensor (PCS) array with 12 adsorptive materials selected from 68 compounds by cluster analysis has been constructed as a perfume odour-sensing system. The frequency shift data obtained from the sensor array responding to four commercial perfume odours are first autoscaled and then treated by principal component analysis. The experimental results show that the plasticized PVC membrane PCS array provides improved performance of pattern recognition compared with the single adsorptive coating PCS array. The frequency shift response characteristics of these sensors have been investigated experimentally. The proposed sensor array has also been applied to the classification of commercial spirituous liquor, wine and soft drink samples, as well as aliphatic alcohol homologues and isomers.     

Solvent colorimetric paper-based polydiacetylene sensors from diacetylene lipids

A well known unique property of polydiacetylenes (PDAs) is the colorimetric response to external stimuli making it one of the most studied conjugated polymers for sensing applications. Here we report the synthesis of a novel series of diacetylene acids from the condensation of pentacosa-10,12-diynylamine (PCDAmine) and dicarboxylic acid or its anhydrides. One of these diacetylene lipids, 4-(pentacosa-10,12-diynylamino)-4-oxobutanoic acid (PCDAS), is used in combination with pentacosa-10,12-diynoic acid (PCDA) for dropcasting on pieces of filter paper which are consequently irradiated by UV light to generate a paper based sensor array for solvent detection and identification. Upon the exposure to various types of organic solvents, the blue colored sensors colorimetrically respond to give different shades of colors between blue to red. The color patterns of the sensor array are recorded as RedGreenBlue (RGB) values and statistically analyzed by principal component analysis (PCA). The PCA score plot reveals that the array is capable of identifying eleven common organic solvents.     

Transduction of glycan-lectin binding using near-infrared fluorescent single-walled carbon nanotubes for glycan profiling

There is significant interest in developing new detection platforms for characterizing glycosylated proteins, despite the lack of easily synthesized model glycans or high affinity receptors for this analytical problem. In this work, we demonstrate a sensor array employing recombinant lectins as glycan recognition sites tethered via Histidine tags to Ni(2+) complexes that act as fluorescent quenchers for semiconducting single-walled carbon nanotubes (SWNTs) embedded in a chitosan hydrogel spot to measure binding kinetics of model glycans. We examine, as model glycans, both free and streptavidin-tethered biotinylated monosaccharides. Two higher-affined glycan-lectin pairs are explored: fucose (Fuc) to PA-IIL and N-acetylglucosamine (GlcNAc) to GafD. The dissociation constants (K(D)) for these pairs as free glycans (106 and 19 μM, respectively) and streptavidin-tethered (142 and 50 μM respectively) were found. The absolute detection limit for the current platform was found to be 2 μg of glycosylated protein or 100 ng of free glycan to 20 μg of lectin. Glycan detection (GlcNAc-streptavidin at 10 μM) is demonstrated at the single nanotube level as well by monitoring the fluorescence from individual SWNT sensors tethered to GafD lectin. Over a population of 1000 nanotubes, 289 of the SWNT sensors had signals strong enough to yield kinetic information (K(D) of 250 ± 10 μM). We are also able to identify the locations of "strong transducers" on the basis of dissociation constant (four sensors with K(D) < 10 μM) or overall signal modulation (eight sensors with >5% quench response). We report the key finding that the brightest SWNTs are not the best transducers of glycan binding. SWNTs ranging in intensity between 50 and 75% of the maximum show the greatest response. The ability to pinpoint strong-binding, single sensors is promising to build a nanoarray of glycan-lectin transducers as a high throughput method to profile glycans without protein labeling or glycan liberation pretreatment steps.     

Evaluation of the performance of sensors based on optical imaging of a chemically sensitive layer

Interest in the use of the optical properties of chemical indicators is growing steadily. Among the optical methods that can be used to capture changes in sensing layers, those producing images of large-area devices are particularly interesting for chemical sensor array development. Until now, few studies addressed the characterization of image sensors from the point of view of their chemical sensor application. In this paper, a method to evaluate such performance is proposed. It is based on the simultaneous measurement of absorption events in a metalloporphyrin layer with an image sensor and a quartz microbalance (QMB). Exploiting the well-known behaviour of QMB, comparison of signals enables estimation of the minimum amount of absorbed molecules that the image sensor can detect. Results indicate that at the single pixel level a standard image sensor (for example a webcam) can easily detect femtomoles of absorbed molecules. It should therefore be possible to design sensor arrays in which the pixels of images of large-area sensing layers are regarded as individual chemical sensors providing a ready and simple method for large sensor array development.