Determination of beta-agonists in swine hair by μFIA and chemiluminescence

Hair and Nail-On-Chip for Bioinspired Microfluidic Device Fabrication and Biomarker Detection

The advent of biosensors has tremendously increased our potential of identifying and solving important problems in various domains, ranging from food safety and environmental analysis, to healthcare and medicine. However, one of the most prominent drawbacks of these technologies, especially in the biomedical field, is to employ conventional samples, such as blood, urine, tissue extracts and other body fluids for analysis, which suffer from the drawbacks of invasiveness, discomfort, and high costs encountered in transportation and storage, thereby hindering these products to be applied for point-of-care testing that has garnered substantial attention in recent years. Therefore, through this review, we emphasize for the first time, the applications of switching over to noninvasive sampling techniques involving hair and nails that not only circumvent most of the aforementioned limitations, but also serve as interesting alternatives in understanding the human physiology involving minimal costs, equipment and human interference when combined with rapidly advancing technologies, such as microfluidics and organ-on-a-chip to achieve miniaturization on an unprecedented scale. The coalescence between these two fields has not only led to the fabrication of novel microdevices involving hair and nails, but also function as robust biosensors for the detection of biomarkers, chemicals, metabolites and nucleic acids through noninvasive sampling. Finally, we have also elucidated a plethora of futuristic innovations that could be incorporated in such devices, such as expanding their applications in nail and hair-based drug delivery, their potential in serving as next-generation wearable sensors and integrating these devices with machine-learning for enhanced automation and decentralization.

A portable automated chip for simultaneous rapid point-of-care testing of multiple β-agonists

Abusive use of β-agonists as feed additives for animals and medication is detrimental to human health and food safety. Conventional assays are restricted to a single type of β-agonists detection and cannot match the multiplexing features to perform automated, high throughput, and rapid quantitative analysis in real samples. In this research, we develop a portable automated chip system (PACS) with highly integrated automated devices in conjunction with portable microfluidic chips to provide simultaneous point-of-care testing of multiple β-agonists in the field, simplifying complex manual methods, shortening assay times, and improving sensitivity. Specifically, silicon film is used as reaction substrates for immobilizing the conjugates of β-agonists to increase the sensitivity of the assay result. Then, the PACS with a chemiluminescence imaging detector is established for automatic high-throughput and sensitive detection of Clenbuterol, Ractopamine, and Salbutamol based on the indirect immunoassay. Newly developed chip with high mixing performance can improve the sensitivity of target determination. Multiplex assays were carried out using the developed system for Clenbuterol, Ractopamine, and Salbutamol with a limit of detection of 54 pg mL-1,59 pg mL-1, and 93 pg mL-1, respectively. Except for sample preparation and coating, the detection in the PACS takes less than 47 min. A satisfactory sample recovery (86.33%-108.12%) was obtained, validating the reliability and practical applicability of this PACS. Meanwhile, the PACS enables sensitive and rapid detection of multiple β-agonists in farms or markets where lacking advanced laboratory facilities.

Electrospun nanofibers modified with zeolitic imidazolate framework-8 for electrochemiluminescent determination of terbutaline

For the first time it is demonstrated that zeolitic imidazolate framework-8 electrospun nanofibers (ZIF-8 NF) could serve as electrochemiluminescence (ECL) accelerator for the facile detection of terbutaline residual. A novel ECL sensor for the determination of terbutaline was fabricated based on ZIF-8 NF. The ZIF-8 NF were successfully prepared according to electrospinning and in-situ growth method. First, chitosan was modified on the surface of the electrode, and then the ZIF-8 NF was modified onto the upper layer of the chitosan. Taking advantages of chitosan and ZIF-8 NF in conductivity and electrocatalysis, the modified electrode presents obvious ECL phenomenon in 0.2 M PBS solution (pH 10.0) containing 0.025 M luminol. After the addition of terbutaline, ECL intensity decreased significantly, and the decreasing value showed a linear relationship with the logarithm of terbutaline concentration. The linear range was from 2.0 × 10^-10 to 2.0 × 10^-5 M, and the detection limit was 1.41 × 10^-11 M (3σ/m). The method had high sensitivity, good stability, and good applicability to actual pork samples.

A novel microfluidic paper-based analytical device based on chemiluminescence for the determination of β-agonists in swine hair

β-Agonists are illegal feed additives in the feed industries of many countries, especially China. Here, we report a microfluidic paper-based analytical device (μPAD) coupled with the chemiluminescence (CL) method to provide the sensitive, simple and rapid quantitative detection of β-agonists in swine hair samples. In this study, we found that the β-agonists diminished the CL generated by the reaction of K3[Fe(CN)6] and luminol on μPAD, which was different from that observed in the aqueous solution, and the degree of diminishment was proportional to the concentration of β-agonists. The possible mechanism was discussed as well. Also, this detection method showed a wide linear range (from 4.0 × 10-8 to 1.0 × 10-5 mol L-1) and low limit of detection (2.0 × 10-8 mol L-1) with a low consumption of samples and reagents. Satisfactory recovery values (from 78% to 95%) were achieved. Therefore, our μPAD CL sensor will be favorable to develop a miniaturized instrument for the on-site analysis of β-agonists in swine hair samples.