Differential sensing for the regio- and stereoselective identification and quantitation of glycerides.

Glycerides are of interest to the areas of food science and medicine because they are the main component of fat. From a chemical sensing perspective, glycerides are challenging analytes because they are structurally similar to one another and lack diversity in terms of functional groups. Furthermore, because animal and plant fat consists of a number of stereo- and regioisomeric acylglycerols, their components remain challenging analytes for chromatographic and mass spectrometric determination, particularly the quantitation of species in mixtures. In this study, we demonstrated the use of an array of cross-reactive serum albumins and fluorescent indicators with chemometric analysis to differentiate a panel of mono-, di-, and triglycerides. Due to the difficulties in identifying the regio- and stereochemistry of the unsaturated glycerides, a sample pretreatment consisting of olefin cross-metathesis with an allyl fluorescein species was used before array analysis. Using this simple assay, we successfully discriminated 20 glycerides via principal component analysis and linear discriminant analysis (PCA and LDA, respectively), including stereo- and regioisomeric pairs. The resulting chemometric patterns were used as a training space for which the structural characteristics of unknown glycerides were identified. In addition, by using our array to perform a standard addition analysis on a mixture of triglycerides and using a method introduced herein, we demonstrated the ability to quantitate glyceride components in a mixture.

Novel Wearable Device for Blood Leakage Detection during Hemodialysis Using an Array Sensing Patch.

Hemodialysis (HD) is a clinical treatment that requires the puncturing of the body surface. However, needle dislodgement can cause a high risk of blood leakage and can be fatal to patients. Previous studies proposed several devices for blood leakage detection using optical or electrical techniques. Nonetheless, these methods used single-point detection and the design was not suitable for multi-bed monitoring. This study proposed a novel wearable device for blood leakage monitoring during HD using an array sensing patch. The array sensing patch combined with a mapping circuit and a wireless module could measure and transmit risk levels. The different risk levels could improve the working process of healthcare workers, and enhance their work efficiency and reduce inconvenience due to false alarms. Experimental results showed that each point of the sensing array could detect up to 0.1 mL of blood leakage and the array sensing patch supports a risk level monitoring system up to 8 h to alert healthcare personnel of pertinent danger to the patients.

Machine Learning-Mediated Ultrasensitive Detection of Citrinin and Associated Mycotoxins in Real Food Samples Discerned from a Photoluminescent Carbon Dot Barcode Array.

Economically viable remote sensing of foodborne contaminants using minimalistic chemical reagents and simultaneous automation calls for a concrete integration of a chemical detection strategy with artificial intelligence. In a first of its kind, we report the ultrasensitive detection of citrinin and associated mycotoxins like aflatoxin B1 and ochratoxin A using an Alizarin Red S (ARS) and cystamine-derived carbon dot (CD) that aptly amalgamate with machine learning algorithms for automation. The photoluminescence response of the CD as a function of various solvents and pH is used to generate array channels that are further modulated in the presence of the mycotoxins whose digital images were acquired to determine pixelation, essentially creating a barcode. The barcode was fed to machine learning algorithms that actualize and intertwine convoluted databases, demonstrating Extreme Gradient Boosting (XGBoost) as the optimized model out of eight algorithms tested. Spiked samples of wheat, rice, gram, maize, coffee, and milk were used to evaluate the testing model where an exemplary accuracy of 100% even at 10 pmol of mycotoxin concentration was achieved. Most importantly, the coexistence of mycotoxins could also be detected through the CD array and XGBoost synergy hinting toward a broader scope of the developed methodology for smart detection of foodborne contaminants.

Nucleotide-selective amplification and array-based detection for identifying multiple somatic mutations.

In the context of personalized and cost-effective treatment, knowledge of the mutational status of specific genes is advantageous to predict which patients are responsive to therapies. As an alternative to one-by-one detection or massive sequencing, the presented genotyping tool determines multiple polymorphic sequences that vary a single nucleotide. The biosensing method includes an effective enrichment of mutant variants and selective recognition by colorimetric DNA arrays. The proposed approach is the hybridization between sequence-tailored probes and products from PCR with SuperSelective primers to discriminate specific variants in a single locus. A fluorescence scanner, a documental scanner, or a smartphone captured the chip images to obtain spot intensities. Hence, specific recognition patterns identified any single-nucleotide change in the wild-type sequence overcoming qPCR methods and other array-based approaches. Studied mutational analyses applied to human cell lines provided high discrimination factors, the precision was 95%, and the sensitivity was 1% mutant of total DNA. Also, the methods showed a selective genotyping of the KRAS gene from tumorous samples (tissue and liquid biopsy), corroborating results by NGS. The developed technology supported on low-cost robust chips and optical reading provides an attractive pathway toward implementing fast, cheap, reproducible discrimination of oncological patients.

Metal-organic framework/3,3',5,5'-tetramethylbenzidine based multidimensional spectral array platform for sensitive discrimination of protein phosphorylation.

A multifunctional metal-organic framework (MOF) hybrid Zr-FeTCPP-MOF is fabricated with 2-aminoterephthalic acid (NH2-BDC) and Fe (III) meso-Tetra (4-carboxyphenyl) porphine chloride (FeTCPPCl) participating in the coordination to Zr6 clusters via one-pot hydrothermal method. The adsorption of phosphoproteins on the surface of Zr-FeTCPP-MOF hybrid cause the chances on the absorbance (Abs), fluorescence (FL) and resonance light scattering (RLS) signals of Zr-FeTCPP-MOF/3,3',5,5'-Tetramethylbenzidine (TMB) system, and an array sensing platform is successfully built for sensitive identification of protein phosphorylation based on the three-dimensional spectral changes of MOF/TMB sensing system induced by the variations on the structure, size, and phosphorylation site of phosphoproteins. This array sensing system is robust in recognizing different phosphoprotein species, and shows high sensitivity in discriminating similar phosphoproteins of different phosphorylation distribution, i.e., caseins (α-, ß- and κ-cas). The detection limit of this array sensing platform to individual phosphoprotein is low down to 5 nM. The practical application of this MOF/TMB-base sensing system is substantially demonstrated by identifying tau peptides with different phosphorylation distribution, and distinguishing cancer cells of abnormal phosphorylations from normal cells. This work proves the reliability, sensitivity, and practicality of the MOF/TMB-base sensing system platform for the diagnosis of phosphorylation-related diseases in clinical trials.