Biosensor Research Articles

Recent advances in developing electrochemical (bio)sensing assays by applying natural polymer-based electrospun nanofibers: A comprehensive review

Electrospinning is a very powerful technique to produce highly complex nanofibers with tunable properties. This technique provides efficiency, versatility, and low cost to create nanofiber assemblies from a rich variety of natural and synthetic polymers combined with different types of nanoparticles. Electrospun nanofiber materials have demonstrated significant potential in various applications, such as sensors and biosensors, tissue engineering, drug delivery, energy conversion, and storage. This is mainly due to their unique characteristics including mechanical strength, large specific surface area, diverse polymer composition, and simple manufacturing process. Nanofiber-based biosensors offer several advantages over conventional biosensors, including enhanced responsiveness, wider linear range, higher sensitivity, lower limit of detection (LOD), and cost-effectiveness. Recently, there has been considerable interest in developing nanobiocomposites by integrating bioreceptors and conductive nanomaterials into carbon, metal oxide, or polymer electrospun nanofibers. In this comprehensive review, we explore advanced biosensors based on electrospinning technology, including biosensors modified with electrospun carbon, metal/metal oxide, as well as polymer-based and polymer-modified biosensors. After a general and short description of the electrospinning process and electrospinning conditions affecting the production of different nanofibers, the application of electrospun nanofibers for the design of electrochemical (bio)sensors is discussed.

Biosensing with Surface-Charge-Modulated Graphene Field-Effect Transistors beyond Nonlinear Electrolytic Screening.

In field-effect transistor (FET) biosensors, charge screening in electrolyte solutions limits the sensitivity, thereby restricting the applicability of FET sensors. This is particularly pronounced in graphene FET (GFET) biosensors, where the bare graphene surface possesses a strongly negative charge, which impedes the high sensitivity of GFETs owing to nonlinear electrolytic screening at the interfaces between graphene and liquid. In this study, we counteracted the negative surface charge of graphene by decorating positively charged compounds and demonstrated the sensing of C-reactive protein (CRP) with surface-charge-modulated GFETs (SCM-GFETs). We integrated multiple SCM-GFETs with anti-CRP antibodies and nonfunctionalized GFETs into a chip and measured differentials to eliminate background changes to improve measurement reliability. The FET response corresponded to the fluorescence images, which visualized the specific adsorption of CRP. The estimated dissociation constant was consistent with previously reported values; this supports the conclusion that the results are attributed to specific adsorption. Conversely, the signal in GFETs without decoration was obscured by noise because of nonlinear electrolytic screening, further emphasizing the significance of surface-charge modulation. The limit of detection of the system was determined to be 2.9 nM. This value has the potential to be improved through further optimization of the surface charges to align with specific applications. Our devices effectively circumvent nonlinear electrolytic screening, opening the door for further advancements in GFET biosensor technology.

Review of: "Biological nano sensors (Nano bio sensor) is the name of a group of sensors"

Review of: "Biological nano sensors (Nano bio sensor) is the name of a group of sensors"

Electrochemical Sensing Based on Nanofibers Modified Electrodes for Application in Diagnostic, Food and Waste Water Samples

AbstractElectrochemical sensors and biosensors are today important analytical and monitoring tools in various fields, from agriculture and the food industry to environmental and biomedical/pharmaceutical applications. In particular, the integration of nanotechnology with electrochemical sensors and biosensors to develop a new generation of sensor platforms has made enormous progress in recent years. The outstanding properties of one‐dimensional (1D) nanofibers (NFs), such as high porosity, superior mechanical properties and high specific surface area have made them attractive electrocatalysts, support materials for the immobilization of biomolecules as well as mimetic materials for sensing and biosensing applications. Moreover, the possibility of fabricating multifunctional composites based on NFs increases (bio)sensing capabilities through synergistic effects and additive properties. This review describes the progress made over the last decade in the use of multifunctional NFs‐based composites as modified electrodes for the sensing of various analytes in biomedical, food, and wastewater treatment applications. The aim of this review is to provide a comprehensive overview and a guide for researchers from different disciplines to fabricate and improve their selective NFs‐based (bio)sensor platforms for the detection of desired analytes or multi‐analytes.

Sensing blood components and cancer cells with photonic crystal resonator biosensor

This study presents the design and numerical analysis of an optical biosensor utilizing a photonic crystal resonator to detect alterations in the refractive index in human blood. The biosensor has potential applications for early diagnosis of cancer cells and various viruses. The structure of the biosensor being proposed is comprised of a waveguide and an oval ring resonator, designed via silicon rods in a 2D square lattice. Accurate detection can lead to choosing the best therapeutic approach and accelerate the patient’s recovery, which is possible by utilizing this biosensor. An optimized and compact design of biosensor (10.2 μm × 7.5 μm) with a significant detection resolution and detection limit of 1∗10-4 , a wide range of cell and virus detection from a refractive index of (1.330 ∼ 1.401) proposed to be implemented in real-time medical applications The proposed sensor has a good figure of merit, and high sensitivity values ranging between 650 and 900. Accordingly, an improved sensor with a quality factor as high as 190 is achieved. Through the implementation of the finite-difference time-domain (FDTD) method, the resonator's reaction to perturbations induced by cells and viruses present in the blood is investigated. The exceptional characteristics of biosensor make it one of the potential candidates in the field of biomedical sensing, which exhibits better sensitivity at the Terahertz band, compared to prior works.

Optical bio sensor based cancer cell detection using optimized machine learning model with quantum computing

Optical bio sensor based cancer cell detection using optimized machine learning model with quantum computing

Complete chiroptical signal detection using weak measurement with intensity-contrast-ratio pointers

Chiroptical signals, including optical rotation (OR) and circular dichroism (CD), are widely utilized as potent probes for investigating the structure and properties of chiral molecules. However, acquiring both coexisting weak OR and CD signals simultaneously in a single measurement process with a high precision remains a challenge for conventional setups. In this article, a high-precision yet easy-to-set-up method for simultaneous detection of OR and CD signals based on weak measurement is theoretically and experimentally demonstrated. In addition, the chiroptical signals are detected using two new intensity-contrast-ratio pointers, which provide an expanded measurement range compared with the shift of the mean value pointer. The proposed method has been validated through a spin Hall effect light based experiment, with precision reaching the order of 10−7 and 10−6 rad for the detection of OR and CD, respectively. These results may serve as a catalyst for further studies of fast, multi-parameter biosensing technologies with ultra-precision.

Analysis on the application of biosensor in forensic detection

This essay simple analysis the advantages and disadvantages of three various biosensor technologies: Gas Chromatography-Mass Spectrometry (GC-MS), Liquid Chromatography-Mass Spectrometry (LC-MS), and Immunoassays. The rapid advancements in biosensing technology have revolutionized for the last few years, these biosensors have revolutionized forensic science by enabling analysis of various compounds, aiding in crime scene investigations, drug testing, and toxicological analysis. Firstly, GC-MS offers outstanding sensitivity and specificity. It allows for the detection of complex mixtures, providing valuable information for identifying substances such as drugs and explosives. However, GC-MS requires time-consuming sample preparation methods, limited applicability to volatile analytes. As well as advanced technical expertise, which can pose challenges for forensic laboratories. Second, LC-MS has shown advantages in analyzing a wide range of non-volatile and polar compounds, making it invaluable in forensic toxicology. LC-MS provides excellent sensitivity and selectivity. Promoting the detection and quantification of pharmaceuticals, illicit drugs, and their metabolites. Lastly, immunoassays provide a simpler and faster substitute for forensic analysis. These assays rely on specific antigen-antibody interactions and are capable of detecting a variety of analytes, such as drugs, hormones and toxins. They offer fast turnaround times, cost effectiveness, and compatibility with point-of-care diagnostics.

Ion Transport in Intelligent Nanochannels: A Comparative Analysis of the Role of Electric Field.

This research delves into investigating ion transport behavior within nanochannels, enhanced through modification with a negatively charged polyelectrolyte layer (PEL), aimed at achieving superior control. The study examines two types of electric fields─direct current and alternating current with square, sinusoidal, triangular, and sawtooth waveforms─to understand their impact on ion transport. Furthermore, the study compares symmetric (cylindrical) and asymmetric (conical) nanochannel geometries to assess the influence of overlapping electrical double layers (EDLs) in generating specific electrokinetic behaviors such as ionic current rectification (ICR) and ion selectivity. The research employs the finite element method to solve the coupled Poisson-Nernst-Planck and Navier-Stokes equations under unsteady-state conditions. By considering factors such as electrolyte concentration, soft layer charge density, and electric field type, the study evaluates ion transport performance in charged nanochannels, investigating effects on concentration polarization, electroosmotic flow (EOF), ion current, rectification, and ion selectivity. Notably, the study accounts for ion partitioning between the PEL and electrolyte to simulate real conditions. Findings reveal that conical nanochannels, due to improved EDL overlap, significantly enhance ion transport and related characteristics compared to cylindrical ones. For instance, under ηε = ηD = 0.8, ημ = 2, C0 = 20 mM, and NPEL/NA = 80 mol m-3 conditions, the average EOF for conical and cylindrical geometries is 0.1 and 0.008 m/s, respectively. Additionally, the study explores ion selectivity and rectification based on the electric field type, unveiling the potential of nanochannels as ion gates or diodes. In cylindrical nanochannels, the ICR remains at unity, with lower ion selectivity across waveforms compared to conical channels. Furthermore, rectification and ion selectivity trends are identified as Rf,square > Rf,DC > Rf,triangular > Rf,sinusoidal > Rf,sawtooth and Ssawtooth > Ssinusoidal > Striangular > SDC > Ssquare for conical nanochannels. Our study of ion transport control in nanochannels, guided by tailored electric fields and unique geometries, offers versatile applications in the field of Analytical Chemistry. This includes enhanced sample separation, controlled drug delivery, optimized pharmaceutical analysis, and the development of advanced biosensing technologies for precise chemical analysis and detection. These applications highlight the diverse analytical contributions of our methodology, providing innovative solutions to challenges in chemical analysis and biosensing.

Assessing Heavy Metal Contamination Using Biosensors and a Multi-Branch Integrated Catchment Model in the Awash River Basin, Ethiopia

Metal pollution in rivers from untreated industrial and domestic wastewater is a major issue in economically developing countries worldwide. The Awash River Basin in Ethiopia is one of those rivers that faces rising heavy metal concentrations due to poor wastewater management and loose law enforcement controlling effluent discharge into rivers. In this study, surface water and wastewater samples were collected within the Awash River Basin, with metals analysis using ICP-MS techniques. Acute toxicity of water was determined using new molecular biosensor technology based on engineered luminescent bacteria. A multi-branch Integrated Catchment Model (INCA) for metals, including Arsenic, Cadmium, Chromium, Copper, Lead, Manganese, and Zinc was applied to the Awash River Basin to simulate the impact of tannery discharge on the river water pollution levels and to evaluate a set of treatment scenarios for pollution control. Results show that all samples from tannery wastewater have high levels of metals, such as Chromium and Manganese with high levels of toxicities. River water samples from upper Awash near Addis Ababa showed elevated concentrations of heavy metals due to the untreated wastewater from the dense population and a large number of industries in that area. The modeling scenarios indicate that improved wastewater management will reduce the metal concentration significantly. With a 50% reduction in effluent concentrations, the mean concentrations of heavy metals (such as Chromium) over two years would be able to reach 20 to 50% reduction in river water samples.

Emerging sensing, imaging, and computational technologies to scale nano-to macroscale rhizosphere dynamics – Review and research perspectives

The soil region influenced by plant roots, i.e., the rhizosphere, is one of the most complex biological habitats on Earth and significantly impacts global carbon flow and transformation. Understanding the structure and function of the rhizosphere is critically important for maintaining sustainable plant ecosystem services, designing engineered ecosystems for long-term soil carbon storage, and mitigating the effects of climate change. However, studying the biological and ecological processes and interactions in the rhizosphere requires advanced integrated technologies capable of decoding such a complex system at different scales. Here, we review how emerging approaches in sensing, imaging, and computational modeling can advance our understanding of the complex rhizosphere system. Particularly, we provide our perspectives and discuss future directions in developing in situ rhizosphere sensing technologies that could potentially correlate local-scale interactions to ecosystem scale impacts. We first review integrated multimodal imaging techniques for tracking inorganic elements and organic carbon flow at nano-to microscale in the rhizosphere, followed by a discussion on the use of synthetic soil and plant habitats that bridge laboratory-to-field studies on the rhizosphere processes. We then describe applications of genetically encoded biosensors in monitoring nutrient and chemical exchanges in the rhizosphere, and the novel nanotechnology-mediated delivery approaches for introducing biosensors into the root tissues. Next, we review the recent progress and express our vision on field-deployable sensing technologies such as planar optodes for quantifying the distribution of chemical and analyte gradients in the rhizosphere under field conditions. Moreover, we provide perspectives on the challenges of linking complex rhizosphere interactions to ecosystem sensing for detecting biological traits across scales, which arguably requires using the best-available model predictions including the model-experiment and image-based modeling approaches. Experimental platforms relevant to field conditions like SMART (Sensors at Mesoscales with Advanced Remote Telemetry) soils testbed, coupled with ecosystem sensing and predictive models, can be effective tools to explore coupled ecosystem behavior and responses to environmental perturbations. Finally, we envision that with the advent of novel high-resolution imaging capabilities spanning from nano-to macroscale, and remote biosensing technologies, combined with advanced computational models, future studies will lead to detection and upscaling of rhizosphere processes toward ecosystem and global predictions.

Microbial Fuel Cells as Effective Tools for Energy Recovery and Antibiotic Detection in Water and Food.

This work demonstrates that microbial fuel cells (MFCs), optimized for energy recovery, can be used as an effective tool to detect antibiotics in water-based environments. In MFCs, electroactive biofilms function as biocatalysts by converting the chemical energy of organic matter, which serves as the fuel, into electrical energy. The efficiency of the conversion process can be significantly affected by the presence of contaminants that act as toxicants to the biofilm. The present work demonstrates that MFCs can successfully detect antibiotic residues in water and water-based electrolytes containing complex carbon sources that may be associated with the food industry. Specifically, honey was selected as a model fuel to test the effectiveness of MFCs in detecting antibiotic contamination, and tetracycline was used as a reference antibiotic within this study. The results show that MFCs not only efficiently detect the presence of tetracycline in both acetate and honey-based electrolytes but also recover the same performance after each exposure cycle, proving to be a very robust and reliable technology for both biosensing and energy recovery.

Application of biosensors against food-borne pathogens

PurposeNature and occurrence of food-borne pathogens in raw and processed food products evolved greatly in the past few years due to new modes of transmission and resistance build-up against sundry micro-/macro-environmental conditions. Assurance of food health and safety thus gained immense importance, for which bio-sensing technology proved very promising in the detection and quantification of food-borne pathogens. Considering the importance, different studies have been performed, and different biosensors have been developed. This study aims to summarize the different biosensors used for the deduction of food-borne pathogens.Design/methodology/approachThe present review highlights different biosensors developed apropos to food matrices, factors governing their selection, their potential and applicability. The paper discusses some related key challenges and constraints and also focuses on the needs and future research prospects in this field.FindingsThe shift in consumers’ and industries’ perceptions directed the further approach to achieve portable, user and environmental friendly biosensing techniques. Despite of these developments, it was still observed that the comparison among the different biosensors and their categories proved tedious on a single platform; since the food matrices tested, pathogen detected or diagnosed, time of detection, etc., varied greatly and very few products have been commercially launched. Conclusively, a challenge lies in front of food scientists and researchers to maintain pace and develop techniques for efficiently catering to the needs of the food industry.Research limitations/implicationsBiosensors deduction limit varied with the food matrix, type of organism, material of biosensors’ surface, etc. The food matrix itself consists of complex substances, and various types of food are available in nature. Considering the diversity of food there is a need to develop a universal biosensor that can be used for all the food matrices for a pathogen. Further research is needed to develop a pathogen-specific biosensor that can be used for all the food products that may have accuracy to eliminate the traditional method of deduction.Originality/valueThe present paper summarized and categorized the different types of biosensors developed for food-borne pathogens.Graphical abstract

Review of: "Biological nano sensors (Nano bio sensor) The human sense of smell and taste"

Review of: "Biological nano sensors (Nano bio sensor) The human sense of smell and taste"

An ANN based biosensor for the detection of Pyrocatechol and hydroquinone in aqueous solutions

This study presents a novel method using an artificial neural network (ANN) to detect Pyrocatechol and hydroquinone in an aqueous solution. The technique utilizes a nanocomposite Poly 3,4-ethylenedioxythiophene-Graphene Oxide Nanosheets (PEDOT-GONs) Laccase biosensor, which demonstrates excellent electrocatalytic activity and electrochemical performance for the redox reactions of the target compounds. The study successfully develops a radical cation electropolymerization process involving poly EDOT with GONs and Lac as dopants to ensure the effective entrapment of the enzymes. Experimental techniques such as electrochemical characterization and SEM confirm the successful entrapment of the enzymes. Further, the ANN was trained using the backpropagation algorithm by applying the experimental results, with current and Pyrocatechol as inputs and hydroquinone concentrations as output. The application of ANN modeling to biosensor technology is validated, demonstrating its utility. The biosensor's linear response detection limit is 0.041 μM within the 0.040–0.41 μM and 0.41–3.0 μM ranges. Finally, the model's performances were evaluated by testing it within the test samples. The performances were measured using precision, recall, accuracy, F1-score, sensitivity, etc., and validated with existing mechanisms.

Remote detection of bovine serum albumin (BSA) using cantilever beam magnetometer

Detection of bovine serum albumin (BSA) is important to comprehend the severity of a certain diseases. Here, we report on the remote detection of bovine serum albumin (BSA) using modified cantilever beam magnetometery (CBM). A magnetostrictive Fe70Ga30 cantilever in combination with optical detection technique allowed us to detect BSA concentration up to 1 mg/mL in a remote way. Essentially, a position sensitive detector (PSD) is used to detect reflected light from cantilever without any optical mirrors. Apart from the above, magnetostriction of Fe70Ga30 cantilever estimated as 80 ppm at 180 mT. We ascertain that our method is easy and efficient in estimating the magnetostriction of thin films up to 10-6 order. We believe that CBM technique that we developed would be helpful in estimating magnetostriction of bulk and thin films apart from the detection of bio – molecules.

Whole-cell biosensor engineering based on the transcription factor XylS/Pm for sensitive detection of PCB intermediate chlorobenzoic acid

Chlorobenzoic acids (Cba) are toxic chloride pollutants commonly released by chemical industries or formed during the degradation pathway of organic chlorides, such as polychlorinated biphenyls (PCBs). Here, we successfully developed a highly sensitive Escherichia coli whole-cell Cba biosensor, named XyF10 (MG1655(DE3)-Ps-XylS (Step13)-Pm1-EGFP), by comprehensive engineering the elements of Cba sensing genetic circuit from Pseudomonas putida. Compared to the native sensing system, XyF10 exhibited a significantly reduced detection limit (<1 μM vs. 50 μM) and an increased signal-to-noise ratio (11.7-fold vs. 4.4-fold), making it a highly efficient whole-cell sensor with the lowest detection limit for Cba reported to date. Structural analysis and molecular dynamics simulations of XylS and its variants revealed that the increased flexibility of a ring structure in XylS (Step13) variant promoted the sensing efficiency of XyF10 system by fascinating the formation of active dimers and enabled more stable binding with inducer. Furthermore, the XyF10 system displayed an obvious preference for meta-substituted Cba (3-Cba) as substrates, which was attributed by the stronger interaction between 3-Cba and the active site of XylS. Overall, our research not only advanced the Cba detection techniques for large-scale detection of Cba in the environment, but also provided potential tools for high-throughput screening of PCB degradation pathways and enzymes.

Biosensors and their widespread impact on human health

‘Give a man a biosensor, and you enable him to unlock a world of cost-effective solutions for research, diagnosis, and personalized healthcare’.Biosensors have emerged as a game-changer in the realms of research sciences and healthcare, offering exceptional value for money. The integration of biosensors into these fields holds immense promise, empowering researchers and medical practitioners to unlock intricate mysteries in food and water safety, human biology, and health assessment. These state-of-the-art technologies are a breath of fresh air, revolutionizing disease detection and tracking to unprecedented levels, elevating the ability to monitor the body's response. They have become the linchpin of numerous cost-effective, highly efficient, and streamlined medical devices prevalent in modern healthcare. By harnessing the sensitivity and specificity of biosensors, healthcare professionals can hit the nail on the head, identifying even the subtlest biomarkers and indicators of various ailments, and enabling timely intervention and treatment. The superior quality of these biosensors ensures unrivaled diagnostic accuracy, leading to more reliable and effective healthcare outcomes. In a nutshell, biosensors have raised the bar, making research, public safety, and tailored healthcare options a walk in the park, ultimately enhancing overall health and well-being.Biosensors offer immense potential in medical diagnostics due to their user-friendly nature, scalability, and efficient manufacturing. With intelligent wearable features, they facilitate seamless health monitoring for the elderly, bridging the gap between self-care and healthcare providers. This exchange of medical information reduces interference and hospital visits, opening avenues in wellness, fitness, and athletics for consumers and commercial entities.This paper explores the advancements in Biosensors technology and their promising benefits in medicine, focusing on cardiovascular diseases and using informative diagrams. It examines fourteen key applications of Biosensors in the medical field, highlighting the integration of biomedical devices, apps, firmware, and advanced algorithms. These developments pave the way for innovative medical therapies, real-time evidence-based insights, customized solutions, and informed guidance, shaping a bright future for healthcare.

Machine learning enabled 2D photonic crystal biosensor for early cancer detection

In this paper, a novel 2D Photonic Crystal (PC)-based cancer biosensor is proposed for the detection of different types of cancer cells HeLa, PC12, MDA, MCF, and Jurkat. The sensor is designed using Silicon-on-insulator (SOI) substrate in a triangular lattice with holes in the slab. The proposed design is optimized to provide a high-quality factor of 15,000, high sensitivity and a low detection limit that are highly effective in cancer detection. Proposed biosensor uses a series of resonant cavities that slice the resonant wavelength to a high peak resonant wavelength with a spectral linewidth of 0.1 nm. The integration of 2D PC biosensors with machine learning techniques for early and accurate cancer detection is optimized for the data set. The performance analysis of Multiple Linear Regression (MLR) and Support Vector Machine (SVM) is studied by repeating training, testing, and optimization of target values (Resonant Wavelength) with dependent and independent features of a 2D PC biosensor system. The SVM modelprovides an R squared value of 0.99 for the biosensor, and the MLR model gave an R squared value of 0.88. TheSVM model provides excellent accuracy in predicting the target values with all the trained input features of a 2D PC biosensing system.

Exploring PAH kinetics in wild vs. transplanted triploid and diploid oysters at a contaminated field site using immunological techniques

Crassostrea virginica is a well-established bivalve species for biomonitoring persistent organic pollutants such as polycyclic aromatic hydrocarbons (PAH) in aquatic environments. Differing biomonitoring methods employing either wild oysters inhabiting sites of interest or naïve cultured oysters deployed to sites for extended periods can be used for site evaluations. However, important differences in total contaminant concentrations accumulated have been observed between the wild and transplanted groups. Furthermore, although rearing cultured triploid oysters is widely popular in commercial farming, the difference in contaminant bioaccumulation potential between triploid and diploid cultured oysters is vastly understudied, particularly for organic contaminants such as PAH. This study explores differences in PAH kinetics between transplanted triploid and diploid cultured oysters and wild oysters at a PAH-impacted site during a 6-week field exposure study using novel immunological techniques: antibody-based biosensor technology and immunofluorescence visualization. Conventional chemical analysis of oyster tissue was also conducted for comparison. While differences were observed in the oyster interstitial fluid between the wild and transplanted oysters throughout the study, whole tissue analysis revealed differing trends at each time point. Our findings suggest that insufficient equilibration time may contribute to the differences observed between groups. Furthermore, when combined with visual evidence via immunofluorescence, internal partitioning of contaminants may be an important determinant for total concentrations measured. A better understanding of the differences observed between wild and transplanted oyster groups is necessary for improved biomonitoring. Our study highlights the value in employing novel immunological techniques to explore possible mechanisms driving these differences.