Electrochemical device based on nonspecific DNAzyme for the high-accuracy determination of Ca2+ with Pb2+ interference

Machine Learning in Bioelectrocatalysis

At present, the global energy crisis and environmental pollution coexist, and the demand for sustainable clean energy has been highly concerned. Bioelectrocatalysis that combines the benefits of biocatalysis and electrocatalysis produces high-value chemicals, clean biofuel, and biodegradable new materials. It has been applied in biosensors, biofuel cells, and bioelectrosynthesis. However, there are certain flaws in the application process of bioelectrocatalysis, such as low accuracy/efficiency, poor stability, and limited experimental conditions. These issues can possibly be solved using machine learning (ML) in recent reports although the combination of them is still not mature. To summarize the progress of ML in bioelectrocatalysis, this paper first introduces the modeling process of ML, then focuses on the reports of ML in bioelectrocatalysis, and ultimately makes a summary and outlook about current issues and future directions. It is believed that there is plenty of scope for this interdisciplinary research direction.

Electrolyte-Gated Graphene Field Effect Transistor-Based Ca2+ Detection Aided by Machine Learning

Flexible electrolyte-gated graphene field effect transistors (Eg-GFETs) are widely developed as sensors because of fast response, versatility and low-cost. However, their sensitivities and responding ranges are often altered by different gate voltages. These bias-voltage-induced uncertainties are an obstacle in the development of Eg-GFETs. To shield from this risk, a machine-learning-algorithm-based LgGFETs' data analyzing method is studied in this work by using Ca²⁺ detection as a proof-of-concept. For the as-prepared Eg-GFET-Ca²⁺ sensors, their transfer and output features are first measured. Then, eight regression models are trained with the use of different machine learning algorithms, including linear regression, support vector machine, decision tree and random forest, etc. Then, the optimized model is obtained with the random-forest-method-treated transfer curves. Finally, the proposed method is applied to determine Ca²⁺ concentration in a calibration-free way, and it is found that the relation between the estimated and real Ca²⁺ concentrations is close-to y = x. Accordingly, we think the proposed method may not only provide an accurate result but also simplify the traditional calibration step in using Eg-GFET sensors.

Superhydrophobic Paper-Based Microfluidic Field-Effect Transistor Biosensor Functionalized with Semiconducting Single-Walled Carbon Nanotube and DNAzyme for Hypocalcemia Diagnosis

Hypocalcemia is caused by a sharp decline in blood calcium concentration after dairy cow calving, which can lead to various diseases or even death. It is necessary to develop an inexpensive, easy-to-operate, reliable sensor to diagnose hypocalcemia. The cellulose-paper-based microfluidic field-effect biosensor is promising for point-of-care, but it has poor mechanical strength and a short service life after exposure to an aqueous solution. Octadecyltrichlorosilane (OTS), as a popular organosilane derivative, can improve the hydrophobicity of cellulose paper to overcome the shortage of cellulose paper. In this work, OTS was used to produce the superhydrophobic cellulose paper that enhances the mechanical strength and short service life of MFB, and a microfluidic field-effect biosensor (MFB) with semiconducting single-walled carbon nanotubes (SWNTs) and DNAzyme was then developed for the Ca²⁺ determination. Pyrene carboxylic acid (PCA) attached to SWNTs through a non-covalent π-π stacking interaction provided a carboxyl group that can bond with an amino group of DNAzyme. Two DNAzymes with different sensitivities were designed by changing the sequence length and cleavage site, which were functionalized with SPFET/SWNTs-PCA to form Dual-MFB, decreasing the interference of impurities in cow blood. After optimizing the detecting parameters, Dual-MFB could determine the Ca²⁺ concentration in the range of 25 μM to 5 mM, with a detection limit of 10.7 μM. The proposed Dual-MFB was applied to measure Ca²⁺ concentration in cow blood, which provided a new method to diagnose hypocalcemia after dairy cow calving.

Electrochemical Biosensor Using Nitrogen-Doped Graphene/Au Nanoparticles/DNAzyme for Ca2+ Determination

An electrochemical biosensor for detecting Ca²⁺ concentration was proposed using glass carbon electrodes (GCEs) modified with nitrogen-doped graphene (NGR), gold nanoparticles (AuNPs) and DNAzyme. The resistance signal was amplified through two methods: electrochemical reduction of AuNPs on the NGR surface to increase the specific surface area of the electrode and strengthen the adsorption of DNAzyme; and increasement of the DNAzyme base sequence. The process of electrode modification was characterized by scanning electron microscopy, Raman spectroscopy, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). Experimental parameters’ influence, such as the deposition time of gold nanoparticles and the detection time, were assessed by electrochemical methods. The linear ranges of the electrochemical biosensor were in the range from 5 × 10⁻⁶ to 5 × 10⁻⁵ and 5 × 10⁻⁵ to 4 × 10⁻⁴ M, with a detection limit of 3.8 × 10⁻⁶ M. The concentration of Ca²⁺ in the serum of dairy cows was determined by the biosensor with satisfactory results, which could be potentially used to diagnose subclinical hypocalcemia.

DNAzyme-Amplified Electrochemical Biosensor Coupled with pH Meter for Ca2+ Determination at Variable pH Environments

For more than 50% of multiparous cows, it is difficult to adapt to the sudden increase in calcium demand for milk production, which is highly likely to cause hypocalcemia. An electrochemical biosensor is a portable and efficient method to sense Ca²⁺ concentrations, but biomaterial is easily affected by the pH of the analyte solution. Here, an electrochemical biosensor was fabricated using a glassy carbon electrode (GCE) and single-walled carbon nanotube (SWNT), which amplified the impedance signal by changing the structure and length of the DNAzyme. Aiming at the interference of the pH, the electrochemical biosensor (GCE/SWNT/DNAzyme) was coupled with a pH meter to form an electrochemical device. It was used to collect data at different Ca²⁺ concentrations and pH values, and then was processed using different mathematical models, of which GPR showed higher detecting accuracy. After optimizing the detecting parameters, the electrochemical device could determine the Ca²⁺ concentration ranging from 5 μM to 25 mM, with a detection limit of 4.2 μM at pH values ranging from 4.0 to 7.5. Finally, the electrochemical device was used to determine the Ca²⁺ concentrations in different blood and milk samples, which can overcome the influence of the pH.

An overview of Structured Biosensors for Metal Ions Determination

The determination of metal ions is important for nutritional and toxicological assessment. Atomic spectrometric techniques are highly efficient for the determination of these species, but the high costs of acquisition and maintenance hinder the application of these techniques. Inexpensive alternatives for metallic element determination are based on dedicated biosensors. These devices mimic biological systems and convert biochemical processes into physical outputs and can be used for the sensitive and selective determination of chemical species such as cations. In this work, an overview of the proposed biosensors for metal ions determination was carried out considering the last 15 years of publications. Statistical data on the applications, response mechanisms, instrumentation designs, applications of nanomaterials, and multielement analysis are herein discussed.