BioChemPen for a Rapid Analysis of Compounds Supported on Solid Surfaces

Automation and Computerization of (Bio)sensing Systems

Sensing systems necessitate automation to reduce human effort, increase reproducibility, and enable remote sensing. In this perspective, we highlight different types of sensing systems with elements of automation, which are based on flow injection and sequential injection analysis, microfluidics, robotics, and other prototypes addressing specific real-world problems. Finally, we discuss the role of computer technology in sensing systems. Automated flow injection and sequential injection techniques offer precise and efficient sample handling and dependable outcomes. They enable continuous analysis of numerous samples, boosting throughput, and saving time and resources. They enhance safety by minimizing contact with hazardous chemicals. Microfluidic systems are enhanced by automation to enable precise control of parameters and increase of analysis speed. Robotic sampling and sample preparation platforms excel in precise execution of intricate, repetitive tasks such as sample handling, dilution, and transfer. These platforms enhance efficiency by multitasking, use minimal sample volumes, and they seamlessly integrate with analytical instruments. Other sensor prototypes utilize mechanical devices and computer technology to address real-world issues, offering efficient, accurate, and economical real-time solutions for analyte identification and quantification in remote areas. Computer technology is crucial in modern sensing systems, enabling data acquisition, signal processing, real-time analysis, and data storage. Machine learning and artificial intelligence enhance predictions from the sensor data, supporting the Internet of Things with efficient data management.

A MnO2 nanosheet-mediated CRISPR/Cas12a system for the detection of organophosphorus pesticides in environmental water

Nowadays, easy, convenient, and sensitive sensing strategies are still critical for organophosphorus pesticides in environmental water samples. Herein, a novel organophosphorus pesticide (OP) assay based on acetylcholinesterase (AChE) and a MnO2 nanosheet-mediated CRISPR/Cas12a reaction is reported. The single-strand DNA (ssDNA) activator of CRISPR/Cas12a was simply adsorbed on the MnO2 nanosheets as the nanoswitches of the assay. In the absence of target OPs, AChE hydrolyzed acetylcholine (ATCh) to thiocholine (TCh), which reduced the MnO2 nanosheets to Mn2+, resulting in the release of the activator followed by activation of the CRISPR/Cas12a system. The activated Cas12a thereafter nonspecifically cleaved the FAM/BHQ1-labeled ssDNA (FQ-reporter), producing a fluorescence signal. Upon the addition of target OPs, the hydrolysis of ATCh by AChE was inhibited owing to OPs combining with AChE, and thus effective quantification of OPs could be achieved by measuring the fluorescence changes of the system. As a proof of concept, dichlorvos (DDVP) was chosen as a model OP analyte to address the feasibility of the proposed method. Attributed to the excellent trans-cleavage activity of Cas12a, the fluorescent biosensor exhibits a satisfactory limit of detection (LOD) for DDVP at 0.135 ng mL-1. In addition, the excellent recoveries for the detection of DDVP in environmental water samples demonstrate the applicability of the proposed assay in real sample research.

Mass Specthoscope: A Hand-held Extendable Probe for Localized Noninvasive Sampling of Skin Volatome for Online Analysis

Human skin emits a unique set of volatile organic compounds (VOCs). These VOCs can be probed in order to obtain physiological information about the individuals. However, extracting the VOCs that emanate from human skin for analysis is troublesome and time-consuming. Therefore, we have developed "Mass Specthoscope"─a convenient tool for rapid sampling and detecting VOCs emitted by human skin. The hand-held probe with a pressurized tip and wireless button enables sampling VOCs from surfaces and their transfer to the atmospheric pressure chemical ionization source of quadrupole time-of-flight mass spectrometer. The system was characterized using chemical standards (acetone, benzaldehyde, sulcatone, α-pinene, and decanal). The limits of detection are in the range from 2.25 × 10-5 to 3.79 × 10-5 mol m-2. The system was initially tested by detecting VOCs emanating from porcine skin spiked with VOCs as well as unspiked fresh and spoiled ham. In the main test, the skin of nine healthy participants was probed with the Mass Specthoscope. The sampling regions included the armpit, forearm, and forehead. Numerous skin-related VOC signals were detected. In the final test, one participant ingested a fenugreek drink, and the participant's skin surface was probed using the Mass Specthoscope hourly during the 8 h period. The result revealed a gradual release of fenugreek-related VOCs from the skin. We believe that this analytical approach has the potential to be used in metabolomic studies and following further identification of disease biomarkers─also in noninvasive diagnostics.

Hydrogel-enzyme micropatch array format for chemical mapping: A proof of concept

Conventional sensing methods report on concentrations of analytes in a single point of sampled medium or provide an average value. However, distributions of substances on surfaces of sampled objects often exhibit intricate inhomogeneities. In order to obtain snapshots of the chemical distributions on surfaces, we have developed enzyme-loaded hydrogel arrays (5 × 5 and 10 × 10). The acrylic 10 × 10 array base contains 100 holes, which are filled with agarose hydrogel containing assay enzymes and substrates. Such arrays can be exposed to the analyzed surfaces to collect minute amounts of analytes. Following a brief incubation, they are subsequently visualized in a custom-built array reader device. The reader incorporates a light-emitting diode-based light source, miniature camera, and Raspberry Pi single-board computer. Two Python programs capture and analyze the images of the array to extract pixel saturation values corresponding to individual hydrogel micropatches. The method has been thoroughly optimized for mapping of glucose and lactic acid. The optimized parameters were: contact time, agarose concentration, substrate concentration, enzyme concentration ratio, and enzyme concentration. The array biosensor was further tested by mapping glucose distribution in fruit/vegetable cross-sections (apple, guava, and cucumber) and lactic acid distribution in cheese. We think that this new hydrogel-based chemical mapping method can find applications in studies related to food science, plant physiology, clinical chemistry, and forensics; wherever the distributions of analytes on the tested surfaces need to be assessed.

Telechemistry 2.0: Remote monitoring of fluorescent chemical reactions

Implementation of the Internet-of-Things in chemistry research has the potential to improve research methodologies. Here, we describe a cloud-integrated real-time laboratory monitoring system for: (i) monitoring reactions involving fluorescent chemical species, and (ii) monitoring laboratory environment for safety purpose. A probe-type fluorescence detection system has been constructed to monitor reactions that involve fluorescent molecules. This device incorporates an in-house-built 3D-printed probe, two optical fibers, a light-emitting diode, a photoresistor, and a microcontroller board (MCB). The MCB relays experimental data to a single-board computer (SBC), which then uploads the data to a cloud-based platform (ThingSpeak) for data storage and visualization. The SBC is also connected to auxiliary sensors to measure relative alcohol vapor concentration, temperature, and humidity at different locations in the laboratory. The device has been validated and tested for its performance by monitoring a fluorescent chemical reaction (synthesis of fluorescent gold nanoclusters) for a period of 12 h.