An Optical Sensor Array Discriminates Syrups and Honeys

Multilocus Distance-Regulated Sensor Array for Recognition of Polyphenols via Machine Learning and Indicator Displacement Assay

Developing new strategies to construct sensor arrays that can effectively distinguish multiple natural components with similar structures in mixtures is an exceptionally challenging task. Here, we propose a new multilocus distance-modulated indicator displacement assay (IDA) strategy for constructing a sensor array, incorporating machine learning optimization to identify polyphenols. An 8-element array, comprising two fluorophores and their six dynamic covalent complexes (C1-C6) formed by pairing two fluorophores with three distinct distance-regulated quenchers, has been constructed. Polyphenols with diverse spatial arrangements and combinatorial forms compete with the fluorophores by forming pseudocycles with quenchers within the complexes, leading to varying degrees of fluorescence recovery. The array accurately and effectively distinguished four tea polyphenols and 16 tea varieties, thereby demonstrating the broad applicability of the multilocus distance-modulated IDA array in detecting polyhydroxy foods and natural medicines.

A facile way to construct sensor array library via supramolecular chemistry for discriminating complex systems

Differential sensing, which discriminates analytes via pattern recognition by sensor arrays, plays an important role in our understanding of many chemical and biological systems. However, it remains challenging to develop new methods to build a sensor unit library without incurring a high workload of synthesis. Herein, we propose a supramolecular approach to construct a sensor unit library by taking full advantage of recognition and assembly. Ten sensor arrays are developed by replacing the building block combinations, adjusting the ratio between system components, and changing the environment. Using proteins as model analytes, we examine the discriminative abilities of these supramolecular sensor arrays. Then the practical applicability for discriminating complex analytes is further demonstrated using honey as an example. This sensor array construction strategy is simple, tunable, and capable of developing many sensor units with as few syntheses as possible.

A poly(arylene ethynylene)-based microfluidic fluorescence sensor array for discrimination of polycyclic aromatic hydrocarbons

Polycyclic aromatic hydrocarbons (PAHs) were discriminated using a microfluidic paper-based sensor array device.

Fluorescent Ensemble Sensors and Arrays Based on Surfactant Aggregates Encapsulating Pyrene-Derived Fluorophores for Differentiation Applications

Surfactant assemblies have drawn great attention in fabricating fluorescent sensors as they can provide advantages such as easy preparation, low cost, aqueous detection, high fluorescence stability, high sensitivity to external stimuli, etc. We have devoted the past few years to fluorescent cross-reactive sensors and arrays that are advantageous in differentiating similar analytes and analyzing mixed samples. In this Spotlight on Applications, we introduce our recent advances in developing surfactant assembly-based fluorescent sensors and arrays for discrimination applications. Besides using surfactant assemblies encapsulating fluorophores to fabricate multiple-element-based sensor arrays, we particularly proposed to take advantage of modulation effect of dynamic surfactant assemblies on the photophysical properties of encapsulated fluorophores to construct single-system-based discriminative sensors, which have been successfully applied in differentiation of multiple metal ions and various proteins. The applications of surfactant assembly-based sensors for the detection and discrimination of thiols, amino acids, and explosives are also introduced. Finally, the prospects of further efforts for improving surfactant ensemble sensors and their challenges are discussed.

Identification of milk adulteration by a sensor array based on cationic polymer induced aggregation of a perylene probe

A novel fluorescence sensor array based on cationic polymer induced self-assembly of a perylene probe is developed. Cationic polymer induced aggregation of the carboxyl modified negatively charged perylene probe, and resulted in large quenching of monomer emission and generation of excimer emission. Upon the addition of negatively charged protein, monomer fluorescence restored with a decrease in excimer fluorescence. Based on these observations, we developed a six-channel sensor array to discriminate five main proteins in milk. In addition, we successfully identified pure milk out of different drinks using the developed sensor array since different drinks contained distinct species and contents of proteins. Furthermore, the sensor array exhibited excellent performance to discriminate milk adulterated by different concentrations of adulterants with 100% accuracy of cross validation. The analysis results also presented excellent linear correlation of adulterants contents and thus the developed sensor array shows great potential for quantitative detection of milk adulteration.

Functional Polymers and Polymer-Dye Composites for Food Sensing

The sensitive, safe, and portable detection of food spoilage is becoming unprecedentedly important because it is closely related to the public health and economic development, particularly given the globalization of food supply chain. However, the existing approaches for food monitoring are still limited to meet these requirements. To address this challenge, much research has been done to develop an ideal food sensor that can indicate food quality in real-time in a sensitive and reliable way. So far, many sensors such as time-temperature indicators, smart trademarks, colorimetric tags, electronic noses, and electronic tongues, have been developed and even commercialized. In this feature article, the recent progress of food sensors based on functional polymers, including the molecular design of polymer structures, sensing mechanisms, and relevant processing techniques to fabricate a variety of food sensor devices is reviewed.

A colorimetric sensor array based on natural pigments for the discrimination of saccharides

A colorimetric sensor array based on natural pigments was developed to discriminate between various saccharides. Anthocyanins, pH-sensitive natural pigments, were extracted from fruits and flowers and used as components of the sensor array. Variation in pH, due to the reaction between saccharides and boronic acids, caused obvious colour changes in the natural pigments. Only by observing the difference map with the naked eye could 11 common saccharides be divided into independent individuals. In conjunction with pattern recognition, the sensor array clearly differentiated between sugar and sugar alcohol with highly accuracy and allowed rapid quantification of different concentrations of maltitol and fructose. This sensor array for saccharides is expected to become a promising alternative tool for food monitoring. The link between anthocyanin and saccharide detection opened a new guiding direction for the application of anthocyanins in foods.

Surfactant and alcohol induced disaggregation of perylene probes and a novel sensing strategy for distinguishing the brand and authenticity of makeup removers

A novel sensing strategy based on four perylene probes to distinguish the brand and authenticity of makeup removers.

Multichannel DNA Sensor Array Fingerprints Cell States and Identifies Pharmacological Effectors of Catabolic Processes

Cells at disease onset are often associated with subtle changes in the expression level of a single or few molecular components, making traditionally used biomarker-driven clinical diagnosis a challenging task. We demonstrate here the design of a DNA nanosensor array with multichannel output that identifies the normal or pathological state of a cell based on the alteration of its global proteomic signature. Fluorophore-encoded single-stranded DNA (ssDNA) strands were coupled via supramolecular interaction with a surface-functionalized gold nanoparticle quencher to generate this integrated sensor array. In this design, ssDNA sequences exhibit dual roles, where they provide differential affinities with the receptor gold nanoparticle as well as act as transducer elements. The unique interaction mode of the analyte molecules disrupts the noncovalent supramolecular complexation, generating simultaneous multichannel fluorescence output to enable signature-based analyte identification via a linear discriminant analysis-based machine learning algorithm. Different cell types, particularly normal and cancerous cells, were effectively distinguished using their fluorescent fingerprints. Additionally, this DNA sensor array displayed excellent sensitivity to identify cellular alterations associated with chemical modulation of catabolic processes. Importantly, pharmacological effectors, which could modulate autophagic flux, have been effectively distinguished by generating responses from their global protein signatures. Taken together, these studies demonstrate that our multichannel DNA nanosensor is well suited for rapid identification of subtle changes in a complex mixture and thus can be readily expanded for point-of-care clinical diagnosis, high-throughput drug screening, or predicting the therapeutic outcome from a limited sample volume.

Fluorescent electronic tongue based on soluble conjugated polymeric nanoparticles for the discrimination of heavy metal ions in aqueous solution

A fluorescence sensing array (or fluorescent electronic tongue) based on six sorts of soluble conjugated polymeric nanoparticles (SCPNs) decorated with PEG chains is designed for the rapid identification of heavy metal ions in water.

Immobilized Poly(aryleneethynylene) pH Strips Discriminate Different Brands of Cola

Fluorescent, water-soluble poly(p-aryleneethynylene)s (PAE) were immobilized on commercially available nylon membranes by using a slot plotter, creating fluorescent, barcode-like sensor strips. Digital imaging by using a standard digital camera, before and after immersion of the strips in buffers of different pH, displays a unique color for each pH value. Statistical evaluation, multivariate analysis of variance (MANOVA) and principal component analysis (PCA), of the acquired data revealed that the immobilized PAEs are superior to the identical fluorophores when dissolved. The pH sensor array discriminates 20 different brands of commercial-cola soft drinks through differences in pH and colorant-PAE interactions.