Ultra-sensitive and label-free neutrophil gelatinase-associated lipocalin electrochemical sensor using gold nanoparticles decorated 3D Graphene foam towards acute kidney injury detection

Non-Invasive Sensors Integration for NCDs with AIoT Based Telemedicine System

Thailand's hospitals face overcrowding, particularly with non-communicable disease (NCD) patients, due to a doctor shortage and an aging population. Most literature showed implementation merely on web or mobile application to teleconsult with physicians. Instead, in this work, we developed and implemented a telemedicine health kiosk system embedded with non-invasive biosensors and time-series predictors to improve NCD indicators over an eight-month period. Two cohorts were randomly selected: a control group with usual care and a telemedicine-using group. The telemedicine-using group showed significant improvements in average fasting blood glucose (148 to 130 mg/dL) and systolic blood pressure (152 to 138 mmHg). Data mining with the Apriori algorithm revealed correlations between diseases, occupations, and environmental factors, informing public health policies. Communication between kiosks and servers used LoRa, 5G, and IEEE802.11, which are selected based on the distance and signal availability. The results support telemedicine kiosks as effective for NCD management, significantly improving key NCD indicators, average blood glucose, and blood pressure.

Empowering an Acute Kidney Injury 3D Graphene-Based Sensor Using Extreme Learning Machine

This study reports on the application of an extreme learning machine (ELM) in near-real-time kidney monitoring via urine neutrophil gelatinase-associated lipocalin (NGAL) detection with a 3D graphene electrode. This integration marks the first instance of combining a graphene-based electrode with machine learning to enhance the NGAL detection accuracy, building on our group's 2020 research. The methodology involves two key components: a graphene electrode functionalized with a lipocalin-2 antibody for NGAL detection and the ELM application for improved prediction accuracy by using urine analysis data. The results show a significant 15% increase in the area under the curve (AUC) for NGAL determination, with error reduction from ±6 to 0.54 ng/mL within a linear range of 2.7-140 ng/mL. The ELM also lowered the detection limit from 14.8 to 0.89 ng/mL and increased accuracy, precision, sensitivity, specificity, and F1 score for AKI prediction by 8.89, 30.69, 6.78, 9.94, and 19.07%, respectively. These findings underscore the efficacy of simple neural networks in enhancing graphene-based electrochemical sensors for AKI biomarkers. ELM was chosen for its optimal performance-resource balance, with a comparative analysis of ELM, support vector machines, multilayer perceptron, and random forest algorithms also included. This research suggests the potential for miniaturizing AI-enhanced sensors for practical applications.

Anomalous Current Steps in 3D Graphene Electrochemical Systems at Room Temperature

In this work, we report a new phenomenon in electrochemical systems whereby uniform current steps of 1 mA per 0.5 × 0.5 × 0.1 cm3 (width × width × depth) of electrode volume occurred during the electrodeposition of gold and silver nanoparticles onto 3D microporous graphene on nickel layers (GF/Ni) at room temperature. The effect was exhibited only at specific applied electrical potentials. The experiments (magnetic interference, temperature dependence, and surface area dependence) were repeated, and the results were reproducible. Finally, we proposed classical electrochemical theory using the Butler-Volmer equation and quantum theory using the Landauer formalism to describe this new effect. Both theories could be used to explain the experimental results: temperature dependence, surface area dependence, blocking effects, and external magnetic field dependence. In addition, the stepwise current presented in this work facilitates the trapping and supplying of a large amount of electric charge via an inherent magnetic field in a sharp time step (∼1 s). A video clip of the recorded effect can be found at https://youtu.be/pPJh45w1sUQ.

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.

Texture or Linker? Competitive Patterning of Receptor Assembly toward Ultra-Sensitive Impedimetric Detection of Viral Species at Gold-Nanotextured Titanium Surfaces

In this work, we study the electrodes with a periodic matrix of gold particles pattered by titanium dimples and modified by 3-mercaptopropionic acid (MPA) followed by CD147 receptor grafting for specific impedimetric detection of SARS-CoV-2 viral spike proteins. The synergistic DFT and MM/MD modeling revealed that MPA adsorption geometries on the Au-Ti surface have preferential and stronger binding patterns through the carboxyl bond inducing an enhanced surface coverage with CD147. Control of bonding at the surface is essential for oriented receptor assembling and boosted sensitivity. The complex Au-Ti electrode texture along with optimized MPA concentration is a crucial parameter, enabling to reach the detection limit of ca. 3 ng mL-1. Scanning electrochemical microscopy imaging and quantum molecular modeling were performed to understand the electrochemical performance and specific assembly of MPA displaying a free stereo orientation and not disturbed by direct interactions with closely adjacent receptors. This significantly limits nonspecific interceptor reactions, strongly decreasing the detection of receptor-binding domain proteins by saturation of binding groups. This method has been demonstrated for detecting the SARS virus but can generally be applied to a variety of protein-antigen systems. Moreover, the raster of the pattern can be tuned using various anodizing processes at the titania surfaces.

Amperometric Biosensor for Quantitative Measurement Using Sandwich Immunoassays

State-of-the-art clinical detection methods typically involve standard immunoassay methods, requiring specialized equipment and trained personnel. This impedes their use in the Point-of-Care (PoC) environment, where ease of operation, portability, and cost efficiency are prioritized. Small, robust electrochemical biosensors provide a means with which to analyze biomarkers in biological fluids in PoC environments. Optimized sensing surfaces, immobilization strategies, and efficient reporter systems are key to improving biosensor detection systems. The signal transduction and general performance of electrochemical sensors are determined by surface properties that link the sensing element to the biological sample. We analyzed the surface characteristics of screen-printed and thin-film electrodes using scanning electron microscopy and atomic force microscopy. An enzyme-linked immunosorbent assay (ELISA) was adapted for use in an electrochemical sensor. The robustness and reproducibility of the developed electrochemical immunosensor were investigated by detecting Neutrophil Gelatinase-Associated Lipocalin (NGAL) in urine. The sensor showed a detection limit of 1 ng/mL, a linear range of 3.5-80 ng/mL, and a CV% of 8%. The results demonstrate that the developed platform technology is suitable for immunoassay-based sensors on either screen-printed or thin-film gold electrodes.

Applications of Transistor-Based Biochemical Sensors

Transistor-based biochemical sensors feature easy integration with electronic circuits and non-invasive real-time detection. They have been widely used in intelligent wearable devices, electronic skins, and biological analyses and have shown broad application prospects in intelligent medical detection. Field-effect transistor (FET) sensors have high sensitivity, reasonable specificity, rapid response, and portability and provide unique signal amplification during biochemical detection. Organic field-effect transistor (OFET) sensors are lightweight, flexible, foldable, and biocompatible with wearable devices. Organic electrochemical transistor (OECT) sensors convert biological signals in body fluids into electrical signals for artificial intelligence analysis. In addition to biochemical markers in body fluids, electrophysiology indicators such as electrocardiogram (ECG) signals and body temperature can also cause changes in the current or voltage of transistor-based biochemical sensors. When modified with sensitive substances, sensors can detect specific analytes, improve sensitivity, broaden the detection range, and reduce the limit of detection (LoD). In this review, we introduce three kinds of transistor-based biochemical sensors: FET, OFET, and OECT. We also discuss the fabrication processes for transistor sources, drains, and gates. Furthermore, we demonstrated three sensor types for body fluid biomarkers, electrophysiology signals, and development trends. Transistor-based biochemical sensors exhibit excellent potential in multi-mode intelligent analysis and are good candidates for the next generation of intelligent point-of-care testing (iPOCT).

Nanoflowers on Microporous Graphene Electrodes as a Highly Sensitive and Low-Cost As(III) Electrochemical Sensor for Water Quality Monitoring

In this work, we report a low-cost and highly sensitive electrochemical sensor for detecting As(III) in water. The sensor uses a 3D microporous graphene electrode with nanoflowers, which enriches the reactive surface area and thus enhances its sensitivity. The detection range achieved was 1-50 ppb, meeting the US-EPA cutoff criteria of 10 ppb. The sensor works by trapping As(III) ions using the interlayer dipole between Ni and graphene, reducing As(III), and transferring electrons to the nanoflowers. The nanoflowers then exchange charges with the graphene layer, producing a measurable current. Interference by other ions, such as Pb(II) and Cd(II), was found to be negligible. The proposed method has potential for use as a portable field sensor for monitoring water quality to control hazardous As(III) in human life.

Electrochemical strategies for the detection of cTnI

Acute myocardial infarction (AMI) is the main cause of death from cardiovascular diseases. Thus, early diagnosis of AMI is essential for the treatment of irreversible damage from myocardial infarction. Traditional electrocardiograms (ECG) cannot meet the specific detection of AMI. Cardiac troponin I (cTnI) is the main biomarker for the diagnosis of myocardial infarction, and the detection of cTnI content has become particularly important. In this review, we introduced and compared the advantages and disadvantages of various cTnI detection methods. We focused on the analysis and comparison of the main indicators and limitations of various cTnI biosensors, including the detection range, detection limit, specificity, repeatability, and stability. In particular, we pay more attention to the application and development of electrochemical biosensors in the diagnosis of cardiovascular diseases based on different biological components. The application of electrochemical microfluidic chips for cTnI was also briefly introduced in this review. Finally, this review also briefly discusses the unresolved challenges of electrochemical detection and the expectations for improvement in the detection of cTnI biosensing in the future.