Design and development of opto-electrochemical biosensing devices for diagnosing chronic kidney disease

Chronic kidney disease (CKD) is emerging as one of the major causes of the increase in mortality rate and is expected to become 5th major cause by 2050. Many studies have shown that it is majorly related to various risk factors, and thus becoming one of the major health issues around the globe. Early detection of renal disease lowers the overall burden of disease by preventing individuals from developing kidney impairment. Therefore, diagnosis and prevention of CKD are becoming the major challenges, and in this situation, biosensors have emerged as one of the best possible solutions. Biosensors are becoming one of the preferred choices for various diseases diagnosis as they provide simpler, cost-effective and precise methods for onsite detection. In this review, we have tried to discuss the globally developed biosensors for the detection of CKD, focusing on their design, pattern, and applicability in real samples. Two major classifications of biosensors based on transduction systems, that is, optical and electrochemical, for kidney disease have been discussed in detail. Also, the major focus is given to clinical biomarkers such as albumin, creatinine, and others related to kidney dysfunction. Furthermore, the globally developed sensors for the detection of CKD are discussed in tabulated form comparing their analytical performance, response time, specificity as well as performance in biological fluids.

Highly Sensitive Detection of Chemically Modified Thio-Organophosphates by an Enzymatic Biosensing Device: An Automated Robotic Approach

Pesticides represent some of the most common man-made chemicals in the world. Despite their unquestionable utility in the agricultural field and in the prevention of pest infestation in public areas of cities, pesticides and their biotransformation products are toxic to the environment and hazardous to human health. Esterase-based biosensors represent a viable alternative to the expensive and time-consuming systems currently used for their detection. In this work, we used the esterase-2 from Alicyclobacillus acidocaldarius as bioreceptor for a biosensing device based on an automated robotic approach. Coupling the robotic system with a fluorescence inhibition assay, in only 30 s of enzymatic assay, we accomplished the detection limit of 10 pmol for 11 chemically oxidized thio-organophosphates in solution. In addition, we observed differences in the shape of the inhibition curves determined measuring the decrease of esterase-2 residual activity over time. These differences could be used for the characterization and identification of thio-organophosphate pesticides, leading to a pseudo fingerprinting for each of these compounds. This research represents a starting point to develop technologies for automated screening of toxic compounds in samples from industrial sectors, such as the food industry, and for environmental monitoring.

Development of an automated multienzymatic biosensor for risk assessment of pesticide contamination in water and food

The goal of this research is to better address the problems related to the widespread presence of pesticides in the environment. Despite the unquestionable utility of the pesticides against various pests in the agricultural field, most pesticides and the corresponding pesticide residues are toxic to the environment and hazardous to human health. The recent literature on organophosphate compounds emphasises a clear correlation between their use and the occurrence of disorders in the nervous system, especially in children. The conventional systems for the detection and analysis of these compounds are expensive, time‐consuming and require highly specialised operators; moreover, no online automated screening systems are yet available, that would allow the identification and quantification of the presence of these chemicals in samples from industrial sectors such as the food industry. Esterase‐based biosensors represent a viable alternative to this problem. In this fellowship programme, we aim to develop a robust and sensitive methodology that enables the screening of toxic compounds using a streamlined process, using an automated robotic system to achieve a continuous monitoring for risk assessment of pesticides.