Computer Vision-Assisted Robotized Sampling of Volatile Organic Compounds.

In conventional chemical analysis, samples are homogenized, extracted, purified, and injected into an analytical instrument manually or with a certain degree of automation. Such complex methods can provide superior performance in terms of sensitivity or selectivity. However, in some cases, it would be advantageous to possess a method that circumvents those preparatory steps, which require much attention. Here, we present a facile analytical approach to sampling volatile organic compounds (VOCs). Solid specimens emitting VOCs can be dropped onto the drop-off zone at a random position without any special alignment. A computer vision system recognizes specimen position, and a robotic arm places a sampling probe in the proximity of the specimen. The probe aspirates the VOCs─emitted by the specimen─with the aid of a suction force. A portion of the gaseous extract is transferred to the tritium-based ion source of a drift-tube ion mobility spectrometer. The ion mobility spectrum is immediately displayed in the customized graphical user interface (GUI). The sampling system also features a function for flushing extract ducts with hot nitrogen gas. Multiple specimens can be dropped for analysis at the same time. In one embodiment, the system can distinguish fresh meat from spoiled meat. When two meat specimens are placed on the drop-off zone, they are immediately sampled by the robotic arm, analyzed, and labeled on the digital image displayed on the GUI. Thus, the developed autosampling platform provides a hassle-free way of qualitative or semiquantitative analysis of raw specimens.

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.

Moderate Signal Enhancement in Electrospray Ionization Mass Spectrometry by Focusing Electrospray Plume with a Dielectric Layer around the Mass Spectrometer's Orifice.

Electrospray ionization (ESI) is among the commonly used atmospheric pressure ionization techniques in mass spectrometry (MS). One of the drawbacks of ESI is the formation of divergent plumes composed of polydisperse microdroplets, which lead to low transmission efficiency. Here, we propose a new method to potentially improve the transmission efficiency of ESI, which does not require additional electrical components and complex interface modification. A dielectric plate-made of ceramic-was used in place of a regular metallic sampling cone. Due to the charge accumulation on the dielectric surface, the dielectric layer around the MS orifice distorts the electric field, focusing the charged electrospray cloud towards the MS inlet. The concept was first verified using charge measurement on the dielectric material surface and computational simulation; then, online experiments were carried out to demonstrate the potential of this method in MS applications. In the online experiment, signal enhancements were observed for dielectric plates with different geometries, distances of the electrospray needle axis from the MS inlet, and various compounds. For example, in the case of acetaminophen (15 µM), the signal enhancement was up to 1.82 times (plate B) using the default distance of the electrospray needle axis from the MS inlet (d = 1.5 mm) and 12.18 times (plate C) using a longer distance (d = 7 mm).

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.

An economical setup for atmospheric pressure chemical ionization drift tube ion-mobility mass spectrometry.

Ion-mobility (IM) separations-performed in conjunction with mass spectrometry (MS)-increase selectivity of MS analyses. However, IM-MS instruments are costly, and many laboratories are only equipped with standard MS instruments without an IM separation stage. Therefore, it is appealing to upgrade the existing mass spectrometers with low-cost IM separation devices. Such devices can be constructed using widely available materials such as printed-circuit boards (PCBs). We demonstrate coupling of an economical PCB-based IM spectrometer (disclosed previously) with a commercial triple quadrupole (QQQ) mass spectrometer. The presented PCB-IM-QQQ-MS system incorporates an atmospheric pressure chemical ionization (APCI) source, drift tube comprising desolvation and drift regions, ion gates, and transfer line to the mass spectrometer. The ion gating is accomplished with the aid of two floated pulsers. The separated ions are divided into packets, which are sequentially introduced to the mass spectrometer. Volatile organic compounds (VOCs) are transferred with the aid of nitrogen gas flow from the sample chamber to the APCI source. The operation of the system has been demonstrated using standard compounds. The limits of detection for 2,4-lutidine, (-)-nicotine, and pyridine are 2.02 × 10-7 M, 1.54 × 10-9 mol, and 4.79 × 10-10 mol, respectively. The system was also used to monitor VOCs emitted from the porcine skin after exposure to nicotine patches, and VOCs released from meat undergoing the spoilage process. We believe this simple APCI-PCB-IM-QQQ-MS platform can be reproduced by others to augment the capabilities of the existing MS instrumentation.

Rapid skin biomarker discovery using hydrogel-phase sampling followed by semi-automated liquid-phase re-extraction high-resolution mass spectrometry.

A facile and rapid skin metabolomics protocol is proposed. The liquid microjunction-surface sampling probe system has been partly automated, and used in conjunction with hydrogel probes for skin metabolite analysis. A control device was built to precisely control the segmented solvent flow and analyte re-extraction into the liquid microjunction. This mode provides rapid online re-extraction of the analytes from hydrogel probes. Humectant was added to the hydrogel, and moist heat treatment was used to make the hydrogel probes rugged for sampling in the clinical setting. The developed method was validated for the analysis of choline - a putative biomarker of psoriasis. A linear relationship over six calibration levels from 3.18 × 10-5 to 3.18 × 10-4 mol m-2 has been obtained. The limit of detection was 6.6 × 10-6 mol m-2, while the recoveries range from 92 to 109%. The within-run and between-run precision were evaluated and the coefficients of variation range from 1.84 to 7.13%. Furthermore, the developed method has been used to screen patients (n = 10) and healthy participants (control group; n = 10) for psoriasis-related skin metabolites. Metabolomic profiling of the skin excretion-related signals identified potential biomarkers of psoriasis: choline, pipecolic acid, ornithine, urocanic acid, and methionine.

Catalytic Oxygenation-Mediated Extraction as a Facile and Green Way to Analyze Volatile Solutes.

Sparging-based methods have long been used to liberate volatile organic compounds (VOCs) from liquid sample matrices prior to analysis. In these methods, a carrier gas is delivered from an external source. Here, we demonstrate "catalytic oxygenation-mediated extraction" (COME), which relies on biocatalytic production of oxygen occurring directly in the sample matrix. The newly formed oxygen (micro)bubbles extract the dissolved VOCs. The gaseous extract is immediately transferred to a separation or detection system for analysis. To start COME, dilute hydrogen peroxide is injected into the sample supplemented with catalase enzyme. The entire procedure is performed automatically-after pressing a "start" button, making a clapping sound, or triggering from a smartphone. The pump, valves, and detection system are controlled by a microcontroller board. For quality control and safety purposes, the reaction chamber is monitored by a camera linked to a single-board computer, which follows the enzymatic reaction progress by analyzing images of foam in real time. The data are instantly uploaded to the internet cloud for retrieval. The COME apparatus has been coupled on-line with the gas chromatography electron ionization mass spectrometry (MS) system, atmospheric pressure chemical ionization (APCI) MS system, and APCI ion-mobility spectrometry system. The three hyphenated variants have been tested in analyses of complex matrices (e.g., fruit-based drinks, whiskey, urine, and stored wastewater). In addition to the use of catalase, COME variants using crude potato pulp or manganese(IV) dioxide have been demonstrated. The technique is inexpensive, fast, reliable, and green: it uses low-toxicity chemicals and emits oxygen.