Comprehensive Review of High Performing Electrochemical Biosensors for Biomedical and Environmental Applications

Since the outbreak of COVID 19 in 2020, being able to detect diseases and chemicals with quick turn-around time becomes ever so needed and important. We have mounted seven different biocatalysts on a sensor platform to examine the performance of this electrochemical sensing system for the detection of different biomolecules/metabolites and environmental important molecules, with such we also compared how this sensing system fares with literature results of similar measurements. The sensor platform constitutes of a layer of bio composite mounted on different electrodes made out of Au, Ag, Pt, and glass carbon; the bio composite is fabricated with polymers and sol-gel Au nanoparticles with or without an extra layer of branching biomolecules. The targeting species for measurements include NH4+, NO3-, CN-, H2O2, and the biomolecules that post specific biomedical functions/identities. In this report, we provide a systematic update of analyses of this sensing system, including the unique identification potentials and sensitivities. This novel sensing system can be a valuable tool in biomedical diagnosis and environmental forensics; in particular the sensor platform used here, any biomedical diagnosis can be conducted with extremely high sensitivity as long as the biomolecules and their antigens are known.

Fe-Based Single-Atom Nanozyme with Superior Peroxidase-Mimicking Activity for Enhanced Ultrasensitive Biosensing

Nanomaterials with intrinsic enzyme-mimicking characteristics, refered to as nanozymes, have become a hot research topic owing to their unique advantages of comparative low cost, high stability and large-scale preparation. Among them, Single-atom nanozymes (SAzymes), as novel nanozymes with abundant atomically dispersed active sites, have caused specific attention in the development of nanozymes for their remarkable catalytic activities, maximum atomic utilization and excellent selectivity, the homogeneous catalytic sites and clear catalytic mechanisms. Herein, a novel single-atom nanozyme based on Fe(III)-doped polydiaminopyridine nanofusiforms (Fe-PDAP SAzyme) was successfully proposed via facile oxidation polymerization strategy. With well-defined coordination structure and abundant Fe-Nx active sites similar to natural metalloproteases, the Fe-PDAP SAzyme exhibits superior peroxidase-like activity by efficiently decomposing H2O2 for hydroxyl radical (.OH) species formation. Based on their superior peroxidase-like activity, colorimetric biosensing of H2O2 and glucose in vitro was performed by using a typical 3,3,5,5-tetramethylbenzidine through a multienzyme biocatalytic cascade platform, exhibiting the superior specificity and sensitivity. This work not only provides a novel promising SAzyme-based biosensor but also paves an avenue for evaluating enzyme activity and broadens the application of other nanozyme-based biosensors in the fields of biomedical diagnosis.

Electrochemical Impedance Spectroscopy (EIS): Principles, Construction, and Biosensing Applications

Electrochemical impedance spectroscopy (EIS) is a powerful technique used for the analysis of interfacial properties related to bio-recognition events occurring at the electrode surface, such as antibody–antigen recognition, substrate–enzyme interaction, or whole cell capturing. Thus, EIS could be exploited in several important biomedical diagnosis and environmental applications. However, the EIS is one of the most complex electrochemical methods, therefore, this review introduced the basic concepts and the theoretical background of the impedimetric technique along with the state of the art of the impedimetric biosensors and the impact of nanomaterials on the EIS performance. The use of nanomaterials such as nanoparticles, nanotubes, nanowires, and nanocomposites provided catalytic activity, enhanced sensing elements immobilization, promoted faster electron transfer, and increased reliability and accuracy of the reported EIS sensors. Thus, the EIS was used for the effective quantitative and qualitative detections of pathogens, DNA, cancer-associated biomarkers, etc. Through this review article, intensive literature review is provided to highlight the impact of nanomaterials on enhancing the analytical features of impedimetric biosensors.

Biosensors: Design, Development and Applications

The ability to detect even the slightest physiological change in the human body with high sensitivity and accurately monitor processes that impact human nature and their surroundings has led to an immense improvement in the quality of life. Biosensors continue to play a critical role across a myriad of fields including biomedical diagnosis, monitoring of treatment and disease progression, drug discovery, food control and environmental monitoring. These novel analytical tools are small devices that use a biological recognition system to investigate or detect molecules. This chapter covers the design and development of biosensors, beginning with a brief historical overview. The working principle and important characteristics or attributes of biosensors will also be addressed. Furthermore, the basic types of biosensors and the general applications of these biosensors in various fields will be discussed.

Biosensors Based Medical Devices For Disease Monitoring Therapy

A Biosensor is a bio-analytical device which is used to collect physical, chemical or biological information and then convert that information into an electrical signal. Nowadays Biosensors are distributed over a considerable extent in biomedical diagnosis and a broad variety of other fields like monitoring of treatment and progression of disease, environment and agriculture monitoring, food safety, discovery of drug, biomedical & forensics research. The first biosensor was designed over a century ago in 1906, but it was clearly defined & established later in 1956. A broad range of techniques can be used for biosensor growth and their combination with high affinity biomolecules enable a variety of analysts to be sensitive & selective. Biosensors and their importance in medical science which includes human’s early stage of detection of interleukin-10 causing heart diseases, fast discovery of human papilloma virus, etc. are various important aspects. Fluorescent biosensors also play a very important role in discovery of drug and in cancer. Biosensor applications are ubiquitous in the plant biology segment to discover out the missing links which is required in metabolic processes. Other applications are implicated in defense, clinical sector, marine applications and also biosensor illustrates the span of bimolecular sensing strategies with the growth of nanotechnology approaches that are now available.

Design of Cyclodextrin-Based Functional Systems for Biomedical Applications

Cyclodextrins (CDs) are a family of α-1,4-linked cyclic oligosaccharides that possess a hydrophobic cavity and a hydrophilic outer surface with abundant hydroxyl groups. This unique structural characteristic allows CDs to form inclusion complexes with various guest molecules and to functionalize with different substituents for the construction of novel sophisticated systems, ranging from derivatives to polymers, metal-organic frameworks, hydrogels, and other supramolecular assemblies. The excellent biocompatibility, selective recognition ability, and unique bioactive properties also make these CD-based functional systems especially attractive for biomedical applications. In this review, we highlight the characteristics and advantages of CDs as a starting point to design different functional materials and summarize the recent advances in the use of these materials for bioseparation, enzymatic catalysis, biochemical sensing, biomedical diagnosis and therapy.

A miniaturized sensing device with ionically imprinted nanostructured films for the ultrasensitive detection of ions

The detection of ions is essential for a wide range of applications including biomedical diagnosis, and environmental monitoring among others. However, current ion sensors are based on thick sensing films (typically 100 µm), requiring time-consuming preparations, and have a thermodynamic limit to their sensitivity of 59 mV.Log[C]-1. Such configuration hinders the development of high-performance ion sensors due to the inherent limitations of the bulk diffusion of ions inside sensors. Consequently, they cannot be applied for high-precision applications that require high sensitivity. Furthermore, the research of anion monitoring is hampered due to the limited availability of molecular receptors with acceptable performances. We overcome such limitations by using a 300 nm nanostructured sensing film based on a novel nanoporous ion imprinted core-shell silica/gold nanoparticulate sensing film. The novel sensing film was highly selective towards chloride ions when compared to other anions such as nitrate, sulphate and carbonate. Moreover, this nanostructured sensing film exhibited above 3-fold higher sensitivity (-186.4 mV.Log[C]-1) towards chloride ions when compared to commercial devices. Such breakthrough has led to the fabrication of the smallest and most sensitive reported anion sensor working on open circuit potentiometry, with an exceptional selectivity towards chloride ions.

Comprehensive Study of Coronavirus Disease 2019 (COVID-19) Classification based on Deep Convolution Neural Networks

Artificial Intelligence (AI) has recently become a topic of study in different applications, including healthcare, in which timely detection of anomalies can play a vital role in patients health monitoring. The coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, colloquially known as the Coronavirus, disrupts large parts of the world. The standard way to test for COVID-19 is Reverse Transcription Polymerase Chain Reaction (RT-PCR), which uses collected samples from the patient. This paper presents an efficient convolution neural network software implementation for COVID-19 and other pneumonia disease detection targeted for an AI-enabled smart biomedical diagnosis system (AIRBiS). From the evaluation results, we found that the classification accuracy of the abnormal (COVID-19 and pneumonia) test dataset is over 97.18%. On the other hand, the accuracy of the normal is no more than 71.37%. We discussed the possible problems and proposals for further optimization.