Biosensors for Detecting Lymphocytes and Immunoglobulins

Anti-IgG Doped Melanin Nanoparticles Functionalized Quartz Tuning Fork Immunosensors for Immunoglobulin G Detection: In Vitro and In Silico Study

The quartz tuning fork (QTF) is a promising instrument for biosensor applications due to its advanced properties such as high sensitivity to physical quantities, cost-effectiveness, frequency stability, and high-quality factor. Nevertheless, the fork's small size and difficulty in modifying the prongs' surfaces limit its wide use in experimental research. Our study presents the development of a QTF immunosensor composed of three active layers: biocompatible natural melanin nanoparticles (MNPs), glutaraldehyde (GLU), and anti-IgG layers, for the detection of immunoglobulin G (IgG). Frequency shifts of QTFs after MNP functionalization, GLU activation, and anti-IgG immobilization were measured with an Asensis QTF F-master device. Using QTF immunosensors that had been modified under optimum conditions, the performance of QTF immunosensors for IgG detection was evaluated. Accordingly, a finite element method (FEM)-based model was produced using the COMSOL Multiphysics software program (COMSOL License No. 2102058) to simulate the effect of deposited layers on the QTF resonance frequency. The experimental results, which demonstrated shifts in frequency with each layer during QTF surface functionalization, corroborated the simulation model predictions. A modelling error of 0.05% was observed for the MNP-functionalized QTF biosensor compared to experimental findings. This study validated a simulation model that demonstrates the advantages of a simulation-based approach to optimize QTF biosensors, thereby reducing the need for extensive laboratory work.

Label-Free Classification of L-Histidine Vs Artificial Human Sweat Using Laser Scribed Electrodes and a Multi-Layer Perceptron Neural Network

A challenge in wearable technology lies in the realtime monitoring of molecular biomarkers associated with human health. Electrochemical sensors are one of the most useful tools for this purpose and are commonly used in health monitoring devices. Electrochemical biosensing is particularly convenient when used in user-friendly, low-cost devices for testing noninvasive body fluids such as sweat and saliva. However, achieving high selectivity and specificity in measurements depends on the complexity of the biomarker and the stability of the biomarker capture molecule. In this study, laser-scribed electrodes (LSEs) were manufactured using a CO2 laser cutter on Polyimide for the label-free classification of sweat components. Cyclic voltammetry experiments were performed on artificial human sweat and the sweat component L-Histidine. The resulting voltammogram data served as input to train a Multi-Layer Perceptron Neural Network (MLP-NN) algorithm capable of classifying L-Histidine and artificial sweat.

Emerging Biosensing Technologies towards Early Sepsis Diagnosis and Management

Sepsis is defined as a systemic inflammatory dysfunction strictly associated with infectious diseases, which represents an important health issue whose incidence is continuously increasing worldwide. Nowadays, sepsis is considered as one of the main causes of death that mainly affects critically ill patients in clinical settings, with a higher prevalence in low-income countries. Currently, sepsis management still represents an important challenge, since the use of traditional techniques for the diagnosis does not provide a rapid response, which is crucial for an effective infection management. Biosensing systems represent a valid alternative due to their characteristics such as low cost, portability, low response time, ease of use and suitability for point of care/need applications. This review provides an overview of the infectious agents associated with the development of sepsis and the host biomarkers suitable for diagnosis and prognosis. Special focus is given to the new emerging biosensing technologies using electrochemical and optical transduction techniques for sepsis diagnosis and management.

A Molecular Study of Aspirin and Tenofovir Using Gold/Dextran Nanocomposites and Surface-Enhanced Raman Spectroscopy

In this study, we show how surface enhanced Raman spectroscopy (SERS) can be used to monitor the molecular behaviour of aspirin and tenofovir as a means of screening medication for quality control purposes. Gold-coated slides combined with gold/dextran nanoaggregates were used to provide signal enhancement of the drugs using SERS. Aspirin (10% w/v) and tenofovir (20% v/v) were analysed in the presence of the nanomaterials to determine trends in molecular response to changes in gold/dextran concentrations. Qualitative analysis of the functional groups showed specific trends where the peak area increased with polarizability, electron density and decreased atomic radii. Steric hinderance effects also affected the trends in peak area due to the amount of gold/dextran nanoparticles in solution. Statistical analysis provided accurate and precise linear relationships (R² = 0.99) for the ester and adenine functional groups of aspirin and tenofovir, respectively. From the above findings, the combined use of gold nano-scaffolds and gold/dextran nanomaterials amplified the Raman signal from the drugs to allow for systematic evaluation of their molecular properties. Although more experiments to correlate the findings are still needed, this SERS approach shows great potential as a screening method in the quality control of medications.