Simple, rapid, and accurate detection methods for saccharides are potentially applicable to various fields such as clinical and food chemistry. However, the practical applications of on-site analytical methods are still limited. To this end, herein, we propose a 96-well microtiter plate made of paper as a paper-based chemosensor array device (PCSAD) for the simultaneous classification of 12 saccharides and the quantification of fructose and glucose among 12 saccharides. The mechanism of the saccharide detection relied on an indicator displacement assay (IDA) on the PCSAD using four types of catechol dyes, 3nitrophenylboronic acid, and the saccharides. The design of the PCSAD and the experimental conditions for the IDA were optimized using a central composite design. The chemosensors exhibited clear color changes upon the addition of saccharides on the paper because of the competitive boronate esterification. The color changes were employed for the subsequent qualitative, semiquantitative, and quantitative analyses using an automated algorithm combined with pattern recognition for digital images. A qualitative linear discrimination analysis offered discrimination of 12 saccharides with a 100% classification rate. The semiquantitative analysis of fructose in the presence of glucose was carried out from the viewpoint of food analysis utilizing a support vector machine, resulting in clear discrimination of the various concentrations of fructose. Most importantly, the quantitative detection of fructose in two types of commercial soft drinks was also successfully carried out without sample pretreatments. Thus, the proposed PCSAD can be a powerful method for on-site food analyses that can meet the increasing demand from consumers for sensors of saccharides.

Although the determination of oxyanions due to correlation with metabolic processes and diseases is in high demand, most of the developed methods are suffering from a shortage of a capability of on-site analysis, sensitivity, and user-friendliness. This paper introduces the first colorimetric chemosensor array targeting various anions including glyphosate. The proposed sensor benefits from some notable features such as utilizing only commercially available reagents, recognizing similarly structured compounds by biomaterial-free sensors, and providing a fingerprint-like response originating from pattern recognition. The detection mechanism is based on an anion sensing strategy named coordination binding-based sensor array (CBSA). In CBSA, competitive coordinative bonding of a metal ion (Zn2+) between a catechol dye (i.e., indicator) and target anions occurs, and changes in the optical properties of the dye represent the target’s concentration. For data processing, two chemometrical techniques including linear discrimination analysis (LDA) and an artificial neural network (ANN) for pattern classification and regression/prediction purposes were successfully employed, respectively. Finally, the proposed chemosensor was subjected to glyphosate samples (commercial herbicide and tap water samples) and produced satisfactory results.

The current work proposes a novel method for accurate pattern recognition of (mono- and di-) amines and determination of enantiomeric excess (ee) using molecular self-assembly.

We believe that “the simpler we are, the more complete we become” is a key concept of chemical sensing systems. In this work, a “turn-on” fluorescence chemosensor array relying on only two self-assembled molecular chemosensors with ability of both qualitative and quantitative detection of phosphorylated saccharides has been developed. The easy-to-prepare chemosensor array was fabricated by in situ mixing of off-the-shelf reagents (esculetin, 4-methylesculetin, and 3-nitrophenylboronic acid). The fluorescence-based saccharide sensing system was carried out using indicator displacement assay accompanied by photoinduced electron transfer (PeT) under various pH conditions. The simultaneous recognition of 14 types of saccharides including glucose-6-phosphate (G6P) and fructose-6-phosphate (F6P) was achieved with a successful classification rate of 100%. We also succeeded in the quantitative analysis of a mixture of glucose (Glc), as an original substrate, G6P and F6P, as enzymatic products in pseudoglycolysis pathway. Finally, levels of Glc and F6P in human induced pluripotent stem (hiPS) cells were indirectly monitored by using our proposed chemosensor array. Glc and F6P in supernatants of hiPS cells were classified by linear discriminant analysis as a pattern recognition model and the observed clusters represent the activity of hiPS cells. The results show the high accuracy of the proposed chemosensor array in detection of phosphorylated and similarly modified saccharides.

This manuscript reports on the application of chemometric methods for the development of an optimized microfluidic paper-based analytical device (μPAD). As an example, we applied chemometric methods for both device optimization and data processing of results of a colorimetric uric acid assay. Box-Behnken designs (BBD) were utilized for the optimization of the device geometry and the amount of thermal inkjet-deposited assay reagents, which affect the assay performance. Measurement outliers were detected in real time by partial least squares discriminant analysis (PLS-DA) of scanned images. The colorimetric assay mechanism is based on the on-device formation of silver nanoparticles (AgNPs) through the interaction of uric acid, ammonia, and poly(vinyl alcohol) with silver ions under mild basic conditions. The yellow color originating from visible light absorption by localized surface plasmon resonance of AgNPs can be detected by the naked eye or, more quantitatively, with a simple flat-bed scanner. Under optimized conditions, the linearity of the calibration curve ranges from 0.1-5 × 10 mol L of uric acid with a limit of detection of 33.9 × 10 mol L and a relative standard of deviation 4.5% (n = 3 for determination of 5.0 × 10 mol L uric acid). Graphical abstract A chemometrics-assisted microfluidic paper-based analytical device was developed as a low-cost and rapid platform for the determination of uric acid (UA). The detection method is based on the chemical interaction of UA, ammonia, and polyvinyl alcohol under mild basic condition with silver ions inducing formation of yellow silver nanoparticles (AgNPs).