Biosensor Applications Research Articles

Photoactivable CRISPR for Biosensing and Cancer Therapy.

Photoactivable CRISPR technology represents a transformative approach in the field of genome editing, offering unprecedented control over gene editing with high spatial and temporal precision. By harnessing the power of light to modulate the activity of CRISPR components, this innovative strategy enables precise regulation of Cas proteins, guide RNAs, and ribonucleoprotein complexes. Recent advancements in optical control methodologies, including the development of photoactivable nanocarriers, have significantly expanded the potential applications of CRISPR in biomedical fields. This Concept highlights the latest developments in designing photoactivable CRISPR systems and their promising applications in biosensing and cancer therapy. Additionally, the remaining challenges and future trends are also discussed. It is expected that the photoactivable CRISPR would facilitate translating more precise gene therapies into clinical use.

GraphBNC: Machine Learning-Aided Prediction of Interactions Between Metal Nanoclusters and Blood Proteins.

Hybrid nanostructures between biomolecules and inorganic nanomaterials constitute a largely unexplored field of research, with the potential for novel applications in bioimaging, biosensing, and nanomedicine. Developing such applications relies critically on understanding the dynamical properties of the nano-bio interface. This work introduces and validates a strategy to predict atom-scale interactions between water-soluble gold nanoclusters (AuNCs) and a set of blood proteins (albumin, apolipoprotein, immunoglobulin, and fibrinogen). Graph theory and neural networks are utilized to predict the strengths of interactions in AuNC-protein complexes on a coarse-grained level, which are then optimized in Monte Carlo-based structure search and refined to atomic-scale structures. The training data is based on extensive molecular dynamics (MD) simulations of AuNC-protein complexes, and the validating MD simulations show the robustness of the predictions. This strategy can be generalized to any complexes of inorganic nanostructures and biomolecules provided that one generates enough data about the interactions, and the bioactive parts of the nanostructure can be coarse-grainedrationally.

Dual-core silver-coated plasmonic sensor modeling with machine learning

Plasmonic sensors utilizing surface plasmon resonance (SPR) have emerged as powerful tools for sensitive and label-free detection across a wide range of applications. This study introduces a new dual-core silver-coated plasmonic sensor designed to significantly enhance sensitivity and resolution, making it particularly effective for precise analyte detection in complex environments. A key innovation of this sensor lies in its dual-core architecture, which achieves the highest wavelength sensitivity reported at 30,000 nm/RIU and resolution of 3.33×10−6 RIU, covering a broad refractive index (RI) range from 1.34 to 1.41. Furthermore, the integration of machine learning (ML) algorithms, including multiple-variable linear regression (MLR), support vector regression (SVR), and random forest regression (RFR), marks a significant advancement in sensor design. These algorithms enable dynamic adaptation and the extraction of data-driven insights, enhancing the sensor's performance in predicting confinement loss and wavelength across various analytes. The innovative combination of a dual-core design and ML integration positions this plasmonic sensor as a highly sensitive and versatile tool well-suited for advanced bio-sensing applications.

Reliable plasmonic biosensing with atmospheric pressure dielectric barrier discharge oxygen plasma treated polydimethylsiloxane microfluidic channels

Polydimethylsiloxane (PDMS) has emerged as a popular choice of material for many microfluidic and flexible sensing devices despite its inherent hydrophobic nature. Here, we report on the use of atmospheric pressure dielectric barrier discharge (APDBD) oxygen (O2) plasma in the development of hydrophilic and protein repulsive PDMS microchannels for plasmonic sensing application. The effect of plasma treatment on the wettability, surface energy and hydrophilicity retention capacity of PDMS was determined using contact angle measurements. The PDMS sample exposed to low-power DBD O2 plasma for 6 min demonstrated lowest contact angle of 35.15˚, surface energy of 62.83 mN/m and hydrophilicity retention capacity of more than 50 days in Phosphate Buffered Saline (PBS). The treatment of PDMS with plasma induces surface hydrophilicity due to the introduction of polar functional groups as evinced by Fourier Transform Infrared (FTIR) analysis without compromising the bulk structure and optical properties of PDMS which were confirmed by X-Ray Diffraction (XRD) and Ultraviolet-visible (UV-Vis) Spectroscopic measurements. The plasma treated PDMS was used in the construction of a microfluidic Surface Plasmon Resonance (SPR) biosensor which demonstrated very low detection limits of 7.13 ng/ml, 5.91 ng/ml and 1.47 ng/ml and high sensitivities of 16.8˚/(µg/ml), 13.5˚/(µg/ml) and 16.65˚/(µg/ml) against anti-Human Immunoglobulin-G protein raised in mouse, goat and rabbit respectively. The obtained results infer that APDBD O2 plasma is a promising technique to render PDMS hydrophilic suited for reliable microfluidic based plasmonic biosensing applications.

A Novel Ferrocene-Linked Thionine as a Dual Redox Mediator for the Electrochemical Detection of Dopamine and Hydrogen Peroxide.

We introduce a novel dual redox mediator synthesized by covalently linking ferrocene dicarboxylic acid (FcDA) and thionine (TH) onto a pre-treated glassy carbon electrode. This unique structure significantly enhances the electro-oxidation of dopamine (DA) and the reduction of hydrogen peroxide (H2O2), offering a sensitive detection method for both analytes. The electrode exhibits exceptional sensitivity, selectivity, and stability, demonstrating potential for practical applications in biosensing. It facilitates rapid electron transfer between the analyte and the electrode surface, detecting H2O2 concentrations ranging from 1.5 to 60 µM with a limit of detection (LoD) of 0.49 µM and DA concentrations from 0.3 to 230 µM with an LoD of 0.07 µM. The electrode's performance was validated through real-sample analyses, yielding satisfactory results.

An intelligent fluorescence sensing platform based on entropy-driven toehold-mediated strand displacement cycle reaction for point-of-care testing of miRNA

BackgroundMicroRNA (miRNA) has gradually become an emerging biomarker for early diagnosis and prognosis of various diseases due to its specific gene expression and high stability. With the development of molecular diagnosis and point-of-care testing (POCT) technology, developing simple, fast, sensitive, efficient, and low-cost miRNA sensors is of great significance for clinical applications and emergency rapid diagnosis. At present, entropy-driven toehold mediated chain displacement reaction, as a promising enzyme free isothermal amplification technique, is an important tool for ultra-sensitive biosensing applications. ResultsIn this study, we used gold nanoparticles (AuNPs) as carriers and quenchers, modified them using self-assembled triple chain composite substrates AuNPs@A@B1/B2, and used dual reporter molecules for cascade cyclic amplification to amplify fluorescence signals, which proposed a fluorescent biosensor based on this reaction and build an intelligent fluorescence sensing platform for rapid detection of miRNA. We designed a highly specific self-programmable sensor using the acute ischemic stroke (AIS) biomarker miRNA-125a-5p as a sample, and achieved sensitive detection of miRNA in the range of 0.01 μM∼10 μ M under optimal conditions. It broke through the traditional detection limitations of weak signals and liberated the fluorescence detection environment. SignificanceIn summary, this creative miRNA biosensor combined with POCT has demonstrated extraordinary detection potential, broad application prospects in the early diagnosis and prognosis monitoring of AIS, provides a novel miRNA universal detection strategy for the fields of biological and life sciences.

Photoswitchable AIE‐Active Supramolecular Self‐Assemblies for Biosensing and Bioimaging

Photoswitchable fluorescent self‐assemblies exhibiting aggregation‐induced emission (AIE) properties have garnered widespread attention. Due to their great adaptiveness and responsiveness towards different wavelengths required by photoreaction, photo‐isomerization, and photoluminescence excitation, these fluorescent self‐assemblies show diverse emission behavior in a spatial, temporal, and polychromatic manner. Integrating organic photoswitches and AIE fluorophores, these photoluminescent nano‐assemblies has been proven to be an effective approach, allowing the development of sophisticated systems for drug release and cell regulation that can be precisely manipulated through light or other stimuli. This review systematically encapsulates recent advances in photoswitchable fluorescent self‐assemblies under multi‐scenario biological applications. The construction of photoswitchable AIE fluorophores through covalent and non‐covalent interactions and their multimodal regulation are detailed, along with their biological applications in biosensing, bioimaging, and drug therapy.

Improving the Efficiency of Luminescent Zn(II)-Modified N-Doped GOQD Nanomaterials in Parkinson's Disease Treatment: A Theoretical Mechanistic Framework Exploring Doping Effect.

Levodopa, a widely prescribed drug in Parkinson's disease treatment, stands as the foremost prodrug of dopamine. An affordable self-testing kit is utilized to monitor levodopa content in anti-parkinson drugs in human serum. A photoluminescent trinuclear Zn(II) complex [Zn3(L)2(κ1-OAc)2(κ2-OAc)2] has been synthesized, which cleaves into mononuclear ZC in aqueous solution. ZC was found to detect L-Dopa in Tris-HCl buffer, exhibiting a moderate decrease in PL-emission. The real-life utility of the ZC probe is limited, for its lower sensitivity (LOD 35.3 μM) and separation challenges. Therefore, an interface between homogeneous and heterogeneous supports has been explored, leading to the strategic development of NGOZC, where ZC was grafted onto NGOQD (Graphene oxide quantum dots). This material enables naked- eye detection under both ambient and UV light with color change from bright cyan to green, followed by dark. The nitrogen doping effect was investigated by several comparative investigations involving the synthesis of ZC-grafted GOQD, leading to enhanced quenching performance. Steady-state and time-resolved fluorescence titration study, morphological analysis, and computational calculations have been performed to get insights into the sensing mechanism. To the best of our knowledge, this as-synthesized NGOZC (LOD 1.78 nM) represents a promising strategy and platform for applications in biosensors, especially for Parkinson's and Alzheimer's diseases.

Fluorescent Iron-Doped Polymer Dot Nanozyme-Based Cascade System for Dual-Mode Detection of Acetylcholinesterase Activity and Its Inhibitors.

The advancement of acetylcholinesterase (AChE) activity and its inhibitor assays is crucial for clinical diagnosis, drug screening, and environmental monitoring. A nanozyme-mediated cascade reaction system could offer promising prospects for a wide range of applications in such biosensing; however, the creation of nanozyme catalysts with diverse functionalities remains a significant challenge. Herein, we have proposed a multifunctional iron-doped polymer dots (Fe-PDs) nanozyme possessing excellent fluorescence and peroxidase (POD)-mimicking activity. Notably, the Fe-PDs nanozyme is capable of catalyzing H2O2 to produce a series of reactive oxygen species, which can simultaneously quench the fluorescence of Fe-PDs and induce a chromogenic reaction of 3,3',5,5'-tetramethylbenzidine (TMB), enabling the dual-mode detection of H2O2 through both fluorescence turn-off and absorbance turn-on signals. Furthermore, by integrating acetylcholine (ACh) and choline oxidase (ChOx), we have developed a three-enzyme (AChE-ChOx-POD) cascade-based fluorometric and colorimetric dual-mode sensing platform for monitoring AChE activity and its inhibitors. The sensitive and convenient dual-mode sensor has achieved low limits of detection with 0.5 mU/mL (fluorometry) and 0.014 mU/mL (colorimetry) for AChE, respectively, which are superior to the traditional Ellman's assay. More significantly, this sensor can also be extended to detect the reversible and irreversible inhibitors of AChE, such as tacrine (IC50 = 23.3 nM) and carbaryl (LOD = 0.8 nM). We firmly believe that this innovative dual-mode nanozyme-involved multienzyme cascade system-based sensing strategy will stimulate further exploration and serve as a versatile and practical tool for biochemical sensing applications.

Detection of Short-Chain Chlorinated Aliphatic Hydrocarbons through an Engineered Biosensor with Tailored Ligand Specificity.

Short-chain chlorinated aliphatic hydrocarbons (SCAHs), commonly used as industrial reagents and solvents, pose a significant threat to ecosystems and human health as they infiltrate aquatic environments due to extensive usage and accidental spills. Whole-cell biosensors have emerged as cost-effective, rapid, and real-time analytical tools for environmental monitoring and remediation. While the broad ligand specificity of transcriptional factors (TFs) often prohibits the application of such biosensors. Herein, we exploited a semirational transition ligand approach in conjunction with a positive/negative fluorescence-activated cell sorting (FACS) strategy to develop a biosensor based on the TF AlkS, which is highly specific for SCAHs. Furthermore, through promoter-directed evolution, the performance of the biosensor was further enhanced. Mutation in the -10 region of constitutive promoter PalkS resulted in reduced AlkS leakage expression, while mutation in the -10 region of inducible promoter PalkB increased its accessibility to the AlkS-SCAHs complex. This led to an 89% reduction in background fluorescence leakage of the optimized biosensor, M2-463, further enhancing its response to SCAHs. The optimized biosensor was highly sensitive and exhibited a broader dynamic response range with a 150-fold increase in fluorescence output after 1 h of induction. The detection limit (LOD) reached 0.03 ppm, and the average recovery rate of SCAHs in actual water samples ranged from 95.87 to 101.20%. The accuracy and precision of the proposed biosensor were validated using gas chromatography-mass spectrometry (GC-MS), demonstrating the promising application for SCAH detection in an actual environment sample.

Tailoring the morphological, optical, electrical, and random lasing properties of ZnO nanorods synthesized on metal surfaces for biosensor applications

Laser-based sensors are taking over their counterparts, fluorescence-based sensors, in the field of bioengineering and space communication due to their high amplification, narrow emission beam, low signal-to-noise ratio, and nonlinearity. In this work, we investigated the chemical growth of ZnO nanorods on different metal surfaces (Au, Pt, Ti, and Al) to serve as random laser mediums. Different analytical techniques were used to investigate the optical, electrical, and morphological properties of the fabricated devices. A lasing threshold of 27.68 mJ/cm² with a spectral width of 2.18 nm centered at 385.06 nm is observed when Ti is used as the growth surface. Al surface produces ZnO nanorods with a lasing threshold of 24.21 mJ/cm² and a spectral width of 1.81 nm. Growing ZnO nanorods on metal surfaces using the chemical bath deposition method paves the way for fabricating different random lasing-based biosensors.

Field effect transistor biosensors for healthcare monitoring

AbstractThe burgeoning demand for healthcare monitoring has brought field effect transistor (FET) biosensors into the spotlight as a highly efficient detection technology. FET biosensors offer inherent advantages including high sensitivity, rapid response times, operational simplicity, integrability, and label‐free detection. These characteristics render them particularly well‐suited for detecting a diverse array of physiological parameters and biomarkers, thereby furnishing real‐time data crucial for personalized medicine and disease prevention. This review aims to elucidate recent advancements in FET biosensors within the realm of healthcare management encompassing several facets. Initially, this review systematically analyzes the device architecture, sensing mechanisms, and performance evaluation methods of FET biosensors to gain an in‐depth understanding of their operational principles and features. Subsequently, it focuses on the application of FET biosensors for detecting health‐related biomarkers encompassing nucleic acids, proteins, exosomes, viruses, etc. Lastly, the review presents engineered medical sensor prototypes predicated on FET biosensors, such as point‐of‐care testing devices, wearable sensors, and implantable sensors, underscoring their practical utility and potential in health management. In addition, the review addresses critical issues and prospects of using FET biosensors in healthcare monitoring, aiming to provide some references and insights for research and innovation in this field.

Design and Simulation of a High-Performance Tunneling Field Effect Transistor-Based Biosensor Using a Heterojunction Electron-Hole Bilayer

Abstract This study introduces a novel dielectrically-modulated heterojunction electron-hole bilayer tunnel field-effect transistor (DM-HEHBTFET) for bio-sensing applications. The device features a Ga0.85Sb0.15As/Ga0.8In0.2As heterojunction and a p-type pocket in the channel, achieving a remarkably low threshold voltage (VT) of 20 mV, an average subthreshold slope (SS) of 5.7 mV/dec, and a leakage current (IOFF) as low as 5 × 10⁻¹¹ A/μm. The staggered bandgap in the heterostructures enhances electric field control, enabling lower gate voltage operation. Furthermore, the strategically positioned nanogap cavities in non-overlapping regions of the top and bottom gates effectively mitigate gate control issues over the channel, ensuring improved device performance. A modified design, the modified DM-HEHBTFET, is also proposed, featuring source and drain regions engineered with Ga0.85Sb0.15As/Ga0.8In0.2As heterojunctions. This design mitigates leakage current and improves the average subthreshold slope (SS). For biomolecules with a dielectric constant of 12, the modified biosensor exhibits a drain current sensitivity (Scurrent) of 2.6e4, average SS=2.7 mV/dec, and IOFF=1e-12 A/μm. The device's performance is assessed by examining steric hindrance and band tailing effects. The modified biosensor outperforms recent DM-TFET biosensors, making it a promising candidate for low-power, high-switching speed bio-sensing.

Dielectric Modulated TFET on SELBOX Substrate as a Label-Free Biosensor Applications: Analytical Modeling Study and Sensitivity Analysis

Abstract The manuscript proposes a ferroelectric heterojunction TFET (BG-FE-HJ-STFET) on SELBOX substrates with a back gate to create an ultra-sensitive label-free biosensor with dielectric modulation for the detection of neutral and charged biomolecules. Within the proposed device, four cavities have been carved out for the biomolecules' immobilization under the front and rear gate dielectrics. By using a ferroelectric (FE) material as a gate stack, the low gate voltage is increased to be more effective by causing a negative capacitance phenomenon. The response of the proposed biosensor to four impartial biomolecules with different dielectric constants Protein (k=8), Biotin (k=2.63), 3-Aminopropyl-triethoxysilane (APTES) (k=3.57), and Streptavidin (k=0.1) has been investigated. Deoxyribonucleic acid (DNA), a charged biomolecule, is also examined for dielectric constant of k=6 with respect to both charges (Negative and Positive)) densities. The device is simulated with the commercially available SILVACO ATLASTM TCAD tool. The performance analysis relies on several figures of merit (FOMs) such as DC/RF and sensitivity (including drain current, ION/IOFF ratio, and subthreshold swing) for both neutral and charged biomolecules. The optimized cavity structure demonstrates a notable sensitivity in drain current (2.7x108) and a significant ION/IOFF sensitivity (1.42x1011). One of the main problems with current biosensors is the difficulty and expense of production in the nanoscale realm.

Neonatal Infectious Disease: A Major Contributor to Infant Mortality Requiring Advances in Point-of-Care Diagnosis.

Neonatal infectious disease continues to result in high rates of infant morbidity and mortality. Early- and late-onset disease represent difficult to detect and difficult to treat illnesses, particularly when antimicrobial resistant pathogens are present. Newborns are immunodeficient and are at increased risk of vertical and horizontal infection, with preterm infants increasingly susceptible. Additional risk factors associated with infection include prolonged use of a central catheter and/or ventilation, congenital abnormalities, admittance to intensive care units, and the use of broad-spectrum antibiotics. There is increasing recognition of the importance of the host microbiome and dysbiosis on neonatal infectious disease, including necrotising enterocolitis and sepsis in patients. Current diagnostic methods rely on blood culture, which is unreliable, time consuming, and can result in false negatives. There is a lack of accurate and reliable diagnostic tools available for the early detection of infectious disease in infants; therefore, efficient triage and treatment remains challenging. The application of biomarkers, machine learning, artificial intelligence, biosensors, and microfluidics technology, may offer improved diagnostic methodologies. Point-of-care devices, such diagnostic methodologies, may provide fast, reliable, and accurate diagnostic aids for neonatal patients. This review will discuss neonatal infectious disease as impacted by antimicrobial resistance and will highlight novel point-of-care diagnostic options.

Systematic Review of IoT-Based Solutions for User Tracking: Towards Smarter Lifestyle, Wellness and Health Management.

The Internet of Things (IoT) base has grown to over 20 billion devices currently operational worldwide. As they greatly extend the applicability and use of biosensors, IoT developments are transformative. Recent studies show that IoT, coupled with advanced communication frameworks, such as machine-to-machine (M2M) interactions, can lead to (1) improved efficiency in data exchange, (2) accurate and timely health monitoring, and (3) enhanced user engagement and compliance through advancements in human-computer interaction. This systematic review of the 19 most relevant studies examines the potential of IoT in health and lifestyle management by conducting detailed analyses and quality assessments of each study. Findings indicate that IoT-based systems effectively monitor various health parameters using biosensors, facilitate real-time feedback, and support personalized health recommendations. Key limitations include small sample sizes, insufficient security measures, practical issues with wearable sensors, and reliance on internet connectivity in areas with poor network infrastructure. The reviewed studies demonstrated innovative applications of IoT, focusing on M2M interactions, edge devices, multimodality health monitoring, intelligent decision-making, and automated health management systems. These insights offer valuable recommendations for optimizing IoT technologies in health and wellness management.

Progress of machine learning-based biosensors for the monitoring of food safety: A review

Rapid urbanization and growing food demand caused people to be concerned about food safety. Biosensors have gained considerable attention for assessing food safety due to selectivity, and sensitivity but poor stability inherently limits their application. The emergence of machine learning (ML) has enhanced the efficiency of different sensors for food safety assessment. The ML combined with various noninvasive biosensors has been implemented efficiently to monitor food safety by considering the stability of bio-recognition molecules. This review comprehensively summarizes the application of ML-powered biosensors to investigate food safety. Initially, different detector-based biosensors using biological molecules with their advantages and disadvantages and biosensor-related various ML algorithms for food safety monitoring have been discussed. Next, the application of ML-powered biosensors to detect antibiotics, foodborne microorganisms, mycotoxins, pesticides, heavy metals, anions, and persistent organic pollutants has been highlighted for the last five years. The challenges and prospects have also been deliberated. This review provides a new prospect in developing various biosensors for multi-food contaminants powered by suitable ML algorithms to monitor in-situ food safety.

Platinum-Selenopeptide Interfaces in Support of High Fidelity Electrochemical Biomarker Quantification in Complex Biological Matrices.

The real world applications of conventional antifouling biosensors based on gold-thiol (Au-S) interfaces are hampered by the progressive competitive displacement of key functionality by ubiquitous biothiols. To overcome this limitation, we introduce here novel platinum-selenium (Pt-Se) interfaces. Thiol displacement tests, antifouling analyses, and density functional theory calculations confirm markedly improved interfacial stability. This was then leveraged through the application of a seleno-multifunctional peptide platform, tailored to the detection of murine double minute 2, in biological samples. A derived amperometric sensing platform exhibited a notably lower detection limit and more accurate target quantification than that supported by analogous Au-S and Pt-S interfaces. We believe that this work broadens the scope of electrochemical sensor construction and holds significant promise for the development of high-fidelity impactful bioassay platforms.

Nanofabrication of Biochar from Cellulosic Waste for Bio-Sensing Application of Waste Water Treatment: Process, Challenges and Future Update

Nanofabrication of Biochar from Cellulosic Waste for Bio-Sensing Application of Waste Water Treatment: Process, Challenges and Future Update

Applications and Challenges of DNA-Based Electrochemical Biosensors for Monitoring Health: A Systematic Review

Applications and Challenges of DNA-Based Electrochemical Biosensors for Monitoring Health: A Systematic Review