Design Of Biosensors Research Articles

Machine learning optimized design of THz piezoelectric perovskite-based biosensor for the detection of formalin in aqueous environments

Abstract This investigation presents the development and characterization of an advanced piezoelectric perovskite-based biosensing platform optimized for formalin detection in aqueous media through the implementation of Locally Weighted Linear Regression (LWLR) machine learning algorithms. The sensor architecture operates within the terahertz spectral region and incorporates an advanced nanomaterial composite system comprising black phosphorus, gold nanostructures, graphene, and barium titanate to maximize detection sensitivity and operational performance metrics. The engineered platform integrates a circular graphene metasurfaces configuration with a gold-based H-resonator assembly and concentrically arranged circular ring resonators. Computational simulations demonstrate vigorous sensing capabilities across three discrete frequency bands, achieving remarkable sensitivity parameters of 444 GHzRIU⁻¹, accompanied by a quality factor of 5.970 and detection accuracy of 7.576. The integration of LWLR-based optimization protocols substantially enhances prediction accuracy while reducing computational time by ≥ 85% as well as cutting down the required resources. The proposed sensor architecture presents significant potential for environmental monitoring and clinical applications, offering a highly sensitive and efficient methodology for quantitative formalin detection in aqueous environments.

Design and Analysis of Surface Plasmon Resonance-Based Refractive Index Biosensor for Detection of Colorectal Cancer with Machine Learning Approach

Design and Analysis of Surface Plasmon Resonance-Based Refractive Index Biosensor for Detection of Colorectal Cancer with Machine Learning Approach

Design and validation of ultra-compact metamaterial-based biosensor for non-invasive cervical cancer diagnosis in terahertz regime.

Cervical cancer belongs to the most dangerous types of cancers posing considerable threat to women's survival. It is most often diagnosed in the advanced stages as precancerous lesions are often symptom-free and difficult to identify. Microwave imaging, especially in terahertz (THz) range, is a convenient and noninvasive cancer detection tool. It enables characterization of biological tissues and discrimination between healthy and malignant ones. This study presents a novel triple-band biosensor based on metamaterials (MTMs). By leveraging unique properties of MTMs, the proposed biosensor operates as a perfect absorber. It exploits resonant modes in the THz spectrum to achieve remarkable sensitivity. Meticulous selection of the sensor geometry and dimensions enables efficient miniaturization. Meanwhile, utilization of frequency-domain data to detect refractive index changes improves resolution of cancerous tissue identification. Extensive numerical investigations corroborate its ability to carry out reliable early-stage cervical cancer diagnosis. This includes identification of the spatial extent of the malignant tissue. Excellent electrical properties of the sensor are accompanied by its compact size, which is highly desirable for non-invasive and portable applications.

Efficient SERS Substrate HOF@Au in Conjunction with DNAzyme-Mediated DNA Walker as a Signal Amplifier for the Ultrasensitive Detection of Lomefloxacin.

Lomefloxacin (LOM) is an efficacious antibiotic that might lead to liver damage and other adverse reactions if consumed over an extended period. Hence, this study proposed a DNAzyme-mediated DNA walker as a signal amplifier in combination with a substantial quantity of Au nanoparticle (NP)-loaded hydrogen-bonded organic frameworks (HOFs) as a surface-enhanced Raman scattering (SERS) substrate to accomplish the highly sensitive detection of LOM in food. Crucially, due to their high specific surface area and strong adsorption capacity, HOFs act as an ideal substrate for the in situ growth of a large amount of Au NPs, which exhibit a robust and uniform SERS enhancement. Once the target LOM was presented, the DNAzyme was activated to start the DNA walker and produce single DNA in abundance, which further triggered the catalytic hairpin assembly (CHA) cycle. In addition, the multi-interstitial core-shell structure of Au@Ag@4-nitrobenzenethiol (4-NTP)@Au@Hp3 produced more SERS "hot spots" and significantly amplified the local electromagnetic field, with HOF@Au synergistically strengthening the Raman signal of 4-NTP. Using this principle, this sensor achieved the ultrasensitive detection of LOM through the "signal on" strategy, with a detection limit as low as 4.62 × 10-14 mol/L. This strategy explored a meaningful innovative path for the design of a novel SERS biosensor for the sensitive and selective detection of antibiotics in food.

Dual Biomarker Strategies for Liquid Biopsy: Integrating Circulating Tumor Cells and Circulating Tumor DNA for Enhanced Tumor Monitoring

The liquid biopsy has gained significant attention in cancer diagnostics, with circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) being recognized as key biomarkers for tumor detection and monitoring. However, each biomarker possesses inherent limitations that restrict its standalone clinical utility, such as the rarity and heterogeneity of CTCs and the variable sensitivity and specificity of ctDNA assays. This highlights the necessity of integrating both biomarkers to maximize diagnostic and prognostic potential, offering a more comprehensive understanding of the tumor biology and therapeutic response. In this review, we summarize clinical studies that have explored the combined analysis of CTCs and ctDNA as biomarkers, providing insights into their synergistic value in diverse tumor types. Specifically, this paper examines the individual advantages and limitations of CTCs and ctDNA, details the findings of combined biomarker studies across various cancers, highlights the benefits of dual biomarker approaches over single-biomarker strategies, and discusses future prospects for advancing personalized oncology through liquid biopsies. By offering a comprehensive overview of clinical studies combining CTCs and ctDNA, this review serves as a guideline for researchers and clinicians aiming to enhance biomarker-based strategies in oncology and informs biosensor design for improved biomarker detection.

Design and Optimization of a Dual-Core GoldCoated PCF-SPR Biosensor for Biosensing Applications

Design and Optimization of a Dual-Core GoldCoated PCF-SPR Biosensor for Biosensing Applications

Design and Analysis of Surface Plasmon Resonance Refractive Index Biosensor with Label-Free Detection of Anemia, HIV, and Cholesterol Samples

Design and Analysis of Surface Plasmon Resonance Refractive Index Biosensor with Label-Free Detection of Anemia, HIV, and Cholesterol Samples

Research progress in the design and application of whole-cell biosensors for antibiotics

Antibiotics are chemicals with bactericidal or bacteriostatic activity produced by microorganisms and artificially synthesized. Since the discovery of penicillin by Alexander Fleming in 1928, antibiotics have been widely used in clinical treatments as well as in the animal husbandry and aquaculture, leading to antibiotic residues in soil, water, food and other environments. At the same time, antibiotic resistance is increasingly serious, which necessitates the discovery of novel antibiotics. In recent years, with the development of synthetic biology, researchers have developed a variety of whole-cell biosensors that can respond to antibiotics. These whole-cell biosensors use microbial cells to convert antibiotic signals into readable signals, which can not only perform dynamic detection of antibiotics simply, quickly, sensitively and accurately but also effectively discover novel antibiotics. This review comprehensively summarizes the reported whole-cell biosensors for antibiotics, classifies them into two types (specific and general), and elaborates on the design principles and applications of the two types of antibiotic biosensors. This review will provide reference for the construction and application of other whole-cell biosensors for antibiotics.

Smart Mesoporous Silica Nanoparticles in Cancer: Diagnosis, Treatment, Immunogenicity, and Clinical Translation.

In cancer research and personalized medicine, mesoporous silica nanoparticles (MSNs) have emerged as a significant breakthrough in both cancer treatment and diagnosis. MSNs offer targeted drug delivery, enhancing therapeutic effectiveness while minimizing adverse effects on healthy cells. Due to their unique characteristics, MSNs provide targeted drug delivery, maximizing therapeutic effectiveness with minimal adverse effects on healthy cells. The review thoroughly investigates the role of MSNs as potent drug carriers, noted for their high drug-loading capacity and controlled release, which significantly improves drug permeability and retention. Additionally, it discusses surface modification techniques that enable MSNs to target cancer cells precisely. The manuscript provides comprehensive insights into various MSN applications, including their role in cancer diagnosis, the design of advanced biosensors, and the development of both conventional and stimuli-responsive drug delivery platforms. Special focus is given to stimuli-triggered MSN systems, responsive to internal stimuli (e.g., pH, redox, enzyme) and external stimuli (e.g., temperature, magnetic field, light, ultrasound), highlighting the cutting-edge progress in MSN technology. Additionally, the review delves into the immunogenicity and biosafety aspects of MSNs, underscoring their potential for clinical translation. Besides summarizing the current state of MSN research in oncology, this review also illuminates the path for future advancements and clinical applications.

Topologically Integrated Photonic Biosensor Circuits

AbstractIntegrated nanophotonic biosensors offer a promising route toward future biomedical detection applications that may enable inexpensive, portable, and sensitive diagnosis of diseases with a small amount of biological samples for convenient early‐stage screening of fatal diseases. However, the current photonic biosensor designs are not suitable for highly integrated and multiplexing device architectures that can achieve the detection of complex combinations of many biomarkers. Here, a topological scheme is proposed for the integration of miniature biosensors in photonic crystal chips that can meet the above requirement. Using photonic topological edge states as robust 1D waveguides that connect many photonic biosensors, here the topologically integrated photonic biosensor circuits is proposed. It is demonstrated that the performance of the topologically integrated photonic biosensors is much more robust against disorders than that of the photonic biosensors connected by the normal photonic waveguides, due to the robust transport of photons along the edge channel. Since disorders arising from the fabrication imperfection and the random distribution of the biomarkers are inevitable in genuine devices, resilience against disorders is a necessity for on‐chip integration of biosensors. The topological scheme proposed here thus opens a promising path toward reliable integration of photonic biosensors for next‐generation biomedical applications.

Illuminating understudied kinases: a generalizable biosensor development method applied to protein kinase N

Protein kinases play crucial roles in regulating cellular processes, making real-time visualization of their activity essential for understanding signaling dynamics. While genetically encoded fluorescent biosensors have emerged as powerful tools for studying kinase activity, their development for many kinases remains challenging due to the lack of suitable substrate peptides. Here, we present a novel approach for identifying peptide substrates and demonstrate its effectiveness by developing a biosensor for Protein Kinase N (PKN) activity. Our method identified a new PKN substrate peptide that we optimized for use in a fluorescent biosensor design. The resulting biosensor shows specificity for PKN family kinases and can detect both overexpressed and endogenous PKN activity in live cells. Importantly, our biosensor revealed sustained basal PKN2 activity at the plasma membrane, identifying it as a PKN2 activity hotspot. This work not only provides a valuable tool for studying PKN signaling but also demonstrates a promising strategy for developing biosensors for other understudied kinases, potentially expanding our ability to monitor kinase activity across the human kinome.

Hexagonal Hollow Core PCF-Based Blood Components Sensing: Design and Simulation.

Blood components play a crucial role in maintaining human health and accurately detecting them is essential for medical diagnostics. A cutting-edge sensor utilizing PCF revealed to precisely identify a wide range of blood components with WBCs (white blood cells), RBCs (red blood cells), HB (hemoglobin), platelets, and plasma. A numerical analysis was performed using COMSOL Multiphysics software to assess the capabilities of the sensor. The sensor design features a hexagonal hollow core-based PCF with a circled air hole operating wavelength from 1.0 μm to 3.0 μm. This innovative PCF sensor exhibits outstanding sensitivity, achieving relative sensitivity values of approximately 97.45% for WBCs, 99.13% for HB, 99.61% for RBCs, 93.44% for plasma, and an impressive 99.42% for platelets, all at a wavelength of 1 μm in its optimized design and this design ensures reliable and highly accurate measurements for various blood components. The corresponding effective areas are 3.32 × 10-11 m2 for WBCs, 2.91 × 10-11 m2 for HB, 2.72 × 10-11 m2 for RBCs, 3.74 × 10-11 m2 for plasma, and 2.79 × 10-11 m2 for platelets, respectively. Furthermore, The sensor demonstrates exceptional performance with remarkably low confinement loss values of 3.032 × 10-9 dB/m for WBCs, 2.947 × 10-9 dB/m for HB, 3.147 × 10-9 dB/m for RBCs, 3.112 × 10-9 dB/m for plasma, and 3.205 × 10-9 dB/m for platelets, respectively. Additionally, the effective material loss is 5.43 × 10-3 cm-1 for WBCs, 2.19 × 10-3 cm-1 for HB, 1.27 × 10-3 cm-1 for RBCs, 1.32 × 10-3 cm-1 for plasma, and 1.58 × 10-3 cm-1 for platelets. Therefore, this biosensor's outstanding sensing capabilities and innovative design make it ideal for industrial and medical applications, ensuring reliability and ease of use. The PCF-based sensor has great potential to transform optical communication applications. Its prosperity model and high sensitivity build it a valued device with the promise of addressing critical challenges in the place of biology, medicine, and communication systems. The sensor features Teflon (tetrafluoroethylene) as its background material, with air holes optimized in a five-ring structure for maximum efficiency and it is the ideal fiber material, offering excellent relative sensitivity and low confinement loss (CL). More than that, 3D printing is the ideal method for fabricating hexagonal hollow-core photonic crystal fiber (PCF) structures, allowing for the effective production of the advanced biosensor design.

Immobilized Saccharomyces cerevisiae viable cells for electrochemical biosensing of Cu(II)

Electrodes functionalised with weak electroactive microorganisms offer a viable alternative to conventional chemical sensors for detecting priority pollutants in bioremediation processes. Biofilm-based biosensors have been proposed for this purpose. However, biofilm formation and maturation require 24–48 h, and the microstructure and coverage of the electrode surface cannot be controlled, leading to poorly reproducible signal and sensitivity. Alternatively, semiconductive biocompatible coatings can be used for viable cell immobilization, achieving reproducible coverage and resulting in a stable biosensor response. In this work, we use a polydopamine (PDA)-based coating to immobilize Saccharomyces cerevisiae yeast viable cells on carbon screen printed electrodes (SPE) for Cu(II) detection, with potassium ferricyanide (K3[Fe (CN)6]) as a redox mediator. Under these conditions, the current output correlates with Cu (II) concentration, reaching a limit of detection of 2.2 µM, as calculated from the chronoamperometric response. The bioelectrochemical results are supported by standard viability assays, microscopy, and electrochemical impedance spectroscopy. The PDA coatings can be functionalised with different mutant strains, thus expanding the toolbox for biosensor design in bioremediation.

Wide Bandwidth High-Power Triboelectric Energy Harvesting by Scotch Tape.

A triboelectric generator was proposed using commercial tape materials, which are composed of metalized poly(ethylene terephthalate) films to serve as electrodes and Scotch tape layers for power generation. Power extraction is achieved by the interaction between polypropylene and the acrylic adhesive layer when pressing and releasing, in which the atomic size gaps are formed due to van der Waals forces at the interface. The proposed triboelectric generator was sandwiched between two plastic plates to lead to a vibration-based energy harvester design with a mass attached to the top. Shaker tests were conducted by varying the vibration frequency, tape layer, and type. A peak power of 45 mW was reached at 40 Hz when using two long-lasting tape layers. The acrylic adhesive layer of long-lasting tape is thicker than other Scotch tapes, which results in higher power generation by the narrowing of atomic gaps. Combining two long-lasting tape layers and two box-lock tape layers produced a 53 mW peak power. Powering of a laser diode was demonstrated at 120 Hz. Current triboelectric generator concept can be applied to a biosensor and acoustic sensor design, as demonstrated in the paper as well.

Negative capacitance source pocket double gate tunnel FET as a label-free dielectrically modulated biosensor

Abstract This article examines the potential use of Negative Capacitance Source Pocket Double Gate Tunnel Field Effect Transistor (NC-SP-DGTFET) as a biosensor capable of detecting the biomolecules present in the nanocavity. The proposed biosensor incorporated a gate dielectric engineering along with the channel engineering method and asymmetrical doping at source and drain regions. In addition, a nanocavity is formed by selectively removing a section of the gate dielectric at the source and drain ends to accompany the biomolecules in the device. The biosensing performance measures Threshold Voltage Sensitivity (S_(V_th )), ION/IOFF Current Ratio Sensitivity (S_(I_oN/I_OFF )), and Drain Current Sensitivity (S_(I_DS )), with 60.3, 372.3, and 395.4 respectively are observed with neutral charge of biomolecules. The investigation involves biomolecules with positive and negative charges, which are tested under different dielectric constants in the nanocavity. In addition, an extensive investigation of a partially filled nanocavity caused by steric hindrance has been presented to capture the current situation. The study examined several scenarios with partially filled nanocavities to analyze the sensitivity characteristics, including convex, concave, increasing, and decreasing step profiles, as well as the positioning of the probe in an asymmetric manner. The study compares several sensitivity characteristics of the NC-SP-DGTFET with existing biosensors to determine the effectiveness of the proposed biosensor. The NC-SP-DGTFET biosensor outperforms traditional TFET-based biosensors by using a ferroelectric material as the oxide material. This choice of material enhances the subthreshold slope, increases gate control over the channel, and demonstrates its suitability for low-power biosensor design.

Design and Optimization of a Two-Component TorRST-Based Biosensor for Detection and Degradation of Trimethylamine N-Oxide.

In mammals, Trimethylamine N-oxide (TMAO) is involved in various physiological processes, and is considered a biomarker for multiple diseases. As a natural molecule found in marine organisms, TMAO is also an important indicator of seafood freshness. In this study, a TMAO biosensor was developed in Escherichia coli harnessing TorRST two-component system. By using a cascade amplification circuit based on HrpRS-PhrpL, the biosensor's dynamic range was increased from 4.1- to 10.3-fold. By optimizing the affinity between the regulatory protein TorR and DNA binding sites in promoters, the concentration for 50% of maximal effect (EC50) value was reduced from 1008 to 141 μM. The biosensor was successfully used for aquatic sample detection. By introducing an exogenous TMAO degradation pathway into E. coli Nissle 1917, a probiotic chassis capable of TMAO detection, transportation, and degradation was constructed, providing an effective tool for rapid detection of TMAO and prevention of multiple diseases.

Graphene-Based Machine Learning–Optimized Surface Plasmon Resonance Biosensor Design for Skin Cancer Detection

Graphene-Based Machine Learning–Optimized Surface Plasmon Resonance Biosensor Design for Skin Cancer Detection

Trends on barrier characteristics improvement of emerging biopolymeric composite films using nanoparticles - A review

BackgroundBio-based films have wide applications in various areas, including medical, packaging, biosensor design, and environmental remediation. Unfortunately, their associated features restricted the application windows for these bio-based films. Barrier properties, such as H2O permeability, O2 permeability, and UV-barrier properties, are among the typical qualities important in designing packaging films because they safeguard food safety and extend shelf life. MethodsEnhancing the barrier qualities has been imperative in recent years owing to its significant impact on food preservation and the valorization of natural biopolymers. The most innovative method is adding metal and metal oxide nanoparticles to the biopolymer with carefully regulated loads and parameters. This review aims to examine the barrier performance as well as their enhancement methods using metal, metal-oxide, and the synergetic effects of nanoparticles. Significant findingsThe review concludes that incorporating metallic and metallic oxide NPs into films has improved their barrier quality. The current and future materials in the property improvement field include metallic and metallic oxide nanoparticles, such as Ag, ZnO, GO, and TiO2, as well as their binary effects. Improvements to the barrier characteristics of bio-based films address the environmental and socioeconomic problems brought on by using petro-based films.

Advances in precise synthesis of metal nanoclusters and their applications in electrochemical biosensing of disease biomarkers.

Metal nanoclusters (NCs), comprising tens to hundreds of metal atoms, are condensed matter with concrete molecular structures and discrete energy levels. Compared to metal atoms and nanoparticles, metal NCs exhibit unique physicochemical properties, especially fascinating electrocatalytic activities. This review focuses on recent progress in the precise synthesis of metal NCs and their applications in electrochemical analysis of various disease biomarkers. First, we provide a brief overview of current nanotechnology-enabled electrochemical biosensors. Subsequently, we highlight the precise synthesis of metal NCs protected by various ligands such as peptides, proteins and nucleic acids. Next, we summarize the design and construction of electrochemical biosensors that utilize metal NCs as electrode materials to detect electrochemically active and inactive disease-associated biomarkers, including small biomolecules (glucose, reactive oxygen species, cholesterol, neurotransmitters and amino acids) and biomacromolecules (proteins, enzymes, and nucleic acids). Due to unique electrocatalytic properties, high specific surface areas, and atomically modulated structures, metal NCs promote electron exchange or act as a redox medium in these electrochemical sensing platforms. Finally, we conclude with present challenges and propose future research directions, with the aim to enhance the specificity, sensitivity, and durability of customized metal NC-based electrochemical biosensors for precise disease diagnostics.

Graphene metasurface biosensor design for label-free peptide detection with machine learning optimization based on support vector regression with polynomial kernel

Graphene metasurface biosensor design for label-free peptide detection with machine learning optimization based on support vector regression with polynomial kernel