Glucose Detection Research Articles

Disposable wireless FET paper sensor based on MWCNT/MXene/MoS2 composite for non-invasive glucose detection in saliva

Disposable wireless FET paper sensor based on MWCNT/MXene/MoS2 composite for non-invasive glucose detection in saliva

Recent progress on nanomaterial-based electrochemical sensors for glucose detection in human body fluids.

In the modern age, half of the population is facing various chronic illnesses due to glucose maintenance in the body, major causes of fatality and inefficiency. The early identification of glucose plays a crucial role in medical treatment and the food industry, particularly in diabetes diagnosis. In the past few years, non-enzymatic electrochemical glucose sensors have received a lot of interest for their ability to identify glucose levels accurately. Electrochemical biosensors are developing as a propitious solution for personalized health monitoring due to their accuracy, specificity, and affordability. This review article provides an observation of a variety of non-enzymatic glucose sensor resources, such as carbon nanomaterials, noble metals gold and silver, transition metal and their oxides, and porous material composites. Moreover, basic knowledge of the reaction mechanism of enzymatic and nonenzymatic glucose sensors are outlined and recent advancements in glucose sensors applicationsto various human body biofluids such as sweat, tears, urine, saliva, and bloodare presented. Finally, this review summarizes electrochemical sensors for glucose detection in human body fluids, the challenges they faced, and their solutions.

Deep Learning-Enhanced Portable Chemiluminescence Biosensor: 3D-Printed, Smartphone-Integrated Platform for Glucose Detection

A novel, portable chemiluminescence (CL) sensing platform powered by deep learning and smartphone integration has been developed for cost-effective and selective glucose detection. This platform features low-cost, wax-printed micro-pads (WPµ-pads) on paper-based substrates used to construct a miniaturized CL sensor. A 3D-printed black box serves as a compact WPµ-pad sensing chamber, replacing traditional bulky equipment, such as charge coupled device (CCD) cameras and optical sensors. Smartphone integration enables a seamless and user-friendly diagnostic experience, making this platform highly suitable for point-of-care (PoC) applications. Deep learning models significantly enhance the platform’s performance, offering superior accuracy and efficiency in CL image analysis. A dataset of 600 experimental CL images was utilized, out of which 80% were used for model training, with 20% of the images reserved for testing. Comparative analysis was conducted using multiple deep learning models, including Random Forest, the Support Vector Machine (SVM), InceptionV3, VGG16, and ResNet-50, to identify the optimal architecture for accurate glucose detection. The CL sensor demonstrates a linear detection range of 10–1000 µM, with a low detection limit of 8.68 µM. Extensive evaluations confirmed its stability, repeatability, and reliability under real-world conditions. This deep learning-powered platform not only improves the accuracy of analyte detection, but also democratizes access to advanced diagnostics through cost-effective and portable technology. This work paves the way for next-generation biosensing, offering transformative potential in healthcare and other domains requiring rapid and reliable analyte detection.

Non-Invasive and Accurate Blood Glucose Detection Based on an Equivalent Bioimpedance Spectrum

Accurate blood glucose monitoring is a key issue for the diagnosis and treatment of diabetes. For this purpose, a non-invasive blood glucose detection method is proposed, which makes use of the equivalent bioelectric impedance spectrum. An impedance detection platform is designed using an automatic balance bridge technique, which can acquire an impedance spectrum within the range of dispersion. Then, the K-nearest neighbor algorithm is used to extract the characteristics of the impedance spectrum. Furthermore, higher-order multiple regression methods are used to establish a blood glucose–electrical impedance spectrum model. Experimental results show that the proposed blood glucose–electrical impedance spectrum model can estimate the change in blood glucose and reliably identify the high blood glucose samples. The correlation between the proposed method and the biochemical blood glucose values can reach 0.89 and 0.87 in personal and multi-person blood glucose tests, respectively. Thus, the proposed method provides a feasible solution for non-invasive blood glucose detection and can help us identify diabetes mellitus.

Stepwise Lighting Up Gold(I)-Thiolate Complexes from AIE Nanoaggregates to AIEE Nanoprobes with a ZIF-8 Shell for Glucose Biosensing.

Aggregation-induced emission (AIE) or aggregation-induced emission enhancement (AIEE) has endowed gold species with responsive fluorescent properties, favoring their potential applications in sensing, imaging, and therapy. However, it remains an interesting challenge to fabricate fluorophores with both AIE and AIEE effects. Herein, we presented highly luminescent Au(I) thiolate nanocomplex-based biosensors with Zn2+ induced-AIE and zeolite imidazolate framework (ZIF-8) induced-AIEE effects. The nonemissive monovalent gold-glutathione complexes (AuI-SGs) were obtained to synthesize the core-shell Zn2+/AuI-SG@ZIF-8 composites with strong luminescence via the coordination-assisted self-assembly strategy. By immobilizing GOx on the surface of Zn2+/AuI-SG@ZIF-8, Zn2+/AuI-SG@ZIF-8/GOx biosensors exhibited effective responsiveness to glucose, showing a "turn-off" detection model. The mechanism study revealed that the robust luminescence of Zn2+/AuI-SG@ZIF-8 to glucose sensing was attributed to the acid-stimulated degradation of the probe facilitated by H+ generated from the glucose oxidase (GOx)-catalyzed oxidation process. To achieve noninvasive and intelligent blood glucose detection, the Zn2+/AuI-SG@ZIF-8/GOx-loaded microneedle (MN)-patch fluorescent platform was further developed. The MN-patch-based sensing platform had promising performance for on-needle capture and in situ glucose detection. This study demonstrated a universal and feasible protocol to construct luminescent biosensors for glucose detection and their potential for the development of MN-based analytical devices.

Molecularly imprinted polymer-based biosensor for detection of salivary glucose in diabetes.

Diabetes is a disorder attributed to impaired production or utilization of insulin and requires rapid precise monitoring of glucose levels. The fabrication of nanotechnology-based non-invasive biosensors for glucose detection holds significant promise for improved diabetes care and point-of-care diagnostics. The study demonstrates a novel molecularly imprinted polymers (ADMIPs) based sensitive biosensor for glucose estimation in saliva using three distinct sensing platforms -cotton swab, paper strip and polymeric film by colorimetric assay. The device employed a TCS3200 RGB sensor for effectively sensing color change based on the presence of D-GSE. Various techniques such as semi-covalent imprinting method, colorimetry, and microcontroller were utilized in device fabrication. The fabricated non-imprinted polymers (ADNIPs) and ADMIPs displayed particle size <1000 nm with quantified glucose readings from saliva via glucose re-binding. Furthermore, ADMIPs were coated onto cotton swabs, paper strips, and polymer films to develop sensing devices with low LODs (0.9 mg/dL - 3.9 mg/dL) and strong correlational values (0.99-0.98) with blood glucose levels in diabetic patients, offering a potential non-invasive alternative for glucose monitoring. These findings highlight the potential utility of MIP-based sensing platforms for non-invasive glucose monitoring in biofluids such as saliva with implications for diabetes management and thorough diagnostic care.

Fabrication of oxides of copper-nickel bimetallic nano particle using Zingiber officnale extract: an eco-friendly approach for electrochemical application of glucose detection

Fabrication of oxides of copper-nickel bimetallic nano particle using Zingiber officnale extract: an eco-friendly approach for electrochemical application of glucose detection

Construction of bimetallic oxy-hydroxides based on Ni(OH)2 nanosheets for sensitive non-enzymatic glucose detection via electrochemical oxidation and incorporation.

Due to their ease of synthesis and large specific surface area, Ni(OH)2 nanosheets have emerged as promising electrochemical sensing materials, attracting significant attention in recent years. Herein, a series of oxy-hydroxides based on Ni(OH)2 nanosheets, including NiOx/Ni(OH)2@NF and (MNi)Ox/Ni(OH)2@NF (M = Co, Fe, or Cr), are successfully synthesized via the electrochemical oxidation and incorporation strategies. Electrochemical tests demonstrate that these Ni(OH)2-based oxy-hydroxides exhibit excellent electrochemical oxidation activity for glucose in alkaline electrolyte. Among these, (CoNi)Ox/Ni(OH)2@NF displays higher sensitivity of 3590.3 μA mM-1 cm-2 across a broad linear range of 10 μM to 1.14 mM, with a rapid current response time of less than 4 s. The superior sensing performances of (CoNi)Ox/Ni(OH)2@NF are attributed to the formation of abundant Ni3+ species and reactive-O atoms due to the electrochemical oxidation, and the synergistic effects of Co/Ni active sites resulting from the electrochemical incorporation process. In addition, the (CoNi)Ox/Ni(OH)2@NF demonstrates good stability and reproducibility for glucose sensing. This work fully leverages the significance of surface reconstruction of Ni(OH)2, providing new insights for the application of transition metal-based oxy-hydroxide materials in bio-sensing.

Correction: An Approach Towards Machine Learning Assisted HEMT Based Quantum Dot Sensor for Glucose Detection

Correction: An Approach Towards Machine Learning Assisted HEMT Based Quantum Dot Sensor for Glucose Detection

Monogenic Diabetes: Genetic Insight and Precision Therapeutics in the Management of MODY

A monogenic diabetes, specifically, the Maturity-onset diabetes of the young (MODY) is the consequence of the single-gene mutations that are responsible for transcription factors such as HNF1A and GCK taking effect on the insulin synthesis, glucose detection, and the formation of beta cells. This genetic basis necessitates a precise clinical approach for accurate diagnosis and personalized treatment, emphasizing precision medicine. Sulfonylureas are a cornerstone treatment for specific MODY subtypes, especially those with KATP channel mutations, as they enhance insulin secretion and alleviate hyperglycemia by targeting the genetic defect. Genetic testing is crucial in identifying the molecular causes of monogenic diabetes, guiding clinicians in tailoring treatment strategies to optimize therapeutic outcomes. This personalized approach integrates genetic insights with precision therapeutics, revolutionizing the management of monogenic diabetes by offering targeted treatments that improve glycemic control and long-term health outcomes. Healthcare professionals can treat patients more effectively and individually by knowing the genetic pathways behind monogenic diabetes. This advances diabetology toward more effective therapeutic strategies. Even the management of diseases can benefit from the invention of precision medicine as applied to the monogenic diabetes, which allows the personalized methods that lead to a positive effect on patients and provide better care to the patient.

PH-Dependent Nonenzymatic Glucose Detection With Pt/Cu₂O Electrodes: Insights From Electrochemical Studies and Matrix Adaptation With Modified Cellulose Fibers

pH-Dependent Nonenzymatic Glucose Detection With Pt/Cu₂O Electrodes: Insights From Electrochemical Studies and Matrix Adaptation With Modified Cellulose Fibers

Enhanced glucose sensing via novel Ni-MOF hybrid structures: Advancements for non-enzymatic wearable glucose sensors

Abstract There is an urgent need of perceptive flexible wearable sensors, for the continuous monitoring of the glucose particularly in a non-invasive way, to control the diabetes at early stages, We have conception of developing non-enzymatic glucose sensing for the detection purpose. Recently, nickel- based metal organic framework (Ni-MOF) has gained a significant importance as a sensing material for label-free, non-enzymatic glucose monitoring using electrochemical sensing techniques. This work, presents a novel state of the art hybridstructure of Ni-MOF consisting of stacked nanosheets embedded with porous nanopillars randomly providing large no. of active sites for the glucose detection. The hybrid structure indicate a close contact between the glucose and the active sites of Ni ions ensuring an efficient glucose sensing. As synthesized Ni-MOF was used for the potentiometric and amperometric electrochemical detection of the glucose using screen-printed electrode (SPE) which are suitable for flexible sensor applications. With SPE, Ni-MOF shows a wide detection range for glucose from 60 µM to 600 µM with the LOD of 0.28 µM and the sensitivity of 4462.03 µA mM-1 cm-2, which is extremely favourable for glucose detection in sweat and saliva of human. The as developed material has potential as a working electrode on the flexible substrate like polyethylene terephthalate (PET), for sensing glucose in sweat and saliva samples.

Anion Bridged One‐Dimensional Copper‐Based Metal Organic Frameworks as Peroxidase Mimics for Glucose Detection in Apple Fruits

ABSTRACTEnzyme mimics attract wide attentions as detection sensors. However, the widespread application is limited by low efficiency and high cost. Herein, two novel enzyme mimics 1 and 2 were developed with peroxidase‐like activities. The chain‐like structure of 1 exhibited better stability, energy transformation efficiency, and catalytic property than 2. Both of them could generate •OH radicals to oxide chromogenic agents, realizing the colorimetric detection of H2O2. Additionally, under the synergy of glucose oxidase, a cascade strategy for detection of glucose was constructed. This method exhibited excellent selectivity, anti‐interference, and storage performance, as well as a wide linear range (1–60 μM) at pH = 7.4, with the low detection limits of 0.095 and 0.061 μM for 1 and 2, respectively. Furthermore, the strategy was applied for detecting glucose in apple fruit samples. This work overcomes the shortcomings of current enzyme mimics and paves the way for bioanalysis and agricultural applications.

Aptamer proximal enzyme cascade reactions for ultrafast detection of glucose in human blood serum.

Aninnovative colorimetric sensing strategy was developedfor the detection of glucose by the integration of glucose aptamer, glucose oxidase (GOx), and horseradish peroxidase (HRP), termed aptamer proximal enzyme cascade reactions (APECR). In the presence of glucose, aptamer binding enables GOx to catalyze glucose oxidation into H2O2 efficiently. Subsequently, the adjacent HRP catalyzes the oxidation of the peroxidase substrate, 2,2'-biazobis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS2-), utilizing the generated H2O2, resulting in a distinct color change. In comparison to the free enzymes and the HRP-GOx system, APECR exhibited higher colorimetric signal. This approach achieved glucose detection within three minutes, which was significantly faster than previous methods. This method showed good sensitivity and selectivity with a limit of detection of 0.013mM. Moreover, the practical utility of this strategy was verified by achieving rapid detection of glucose in clinical serum samples. Hence, the developed strategy has the advantages of simple operation and rapid analysis time for the detection of glucose in human serum.

Copper‐Loaded Nitrogen‐Rich Mesoporous C3N6 Based Nanozymes for Calorimetric Detection of Glutathione and Glucose

AbstractBiomolecular sensing is routinely implemented in healthcare industries for disease diagnostics. Copper nanoparticles efficiently mimic peroxidase, which is needed for efficient glucose and glutathione sensing. However, bare copper nanoparticles are toxic to humans, therefore, anchoring materials are needed to prevent health hazards. Among the carbon‐based anchoring materials, graphene and its derivatives have already been implemented. However, due to poor C–Cu interaction, copper incorporation is inefficient in those systems, which necessitates the exploration of new suitable anchoring platforms. Nitrogen‐rich carbon nitride C3N6 with edge nitrogen atoms and plenty of in‐built vacancy sites in its lattice, apart from its facile synthesis, low cost, scalable production, and non‐toxic nature; offers excellent candidature for this purpose. Cu‐loaded mC3N6 (Cu‐mC3N6) nanozyme is synthesized employing hard silica template SBA‐15 and aminoguanidine hydrochloride and hydrated copper nitrate. First, peroxidase‐like activity is investigated for Cu‐mC3N6 nanozyme with chromogenic 3,3′,5,5′‐ tetramethylbenzidine (TMB) dye, followed by calorimetric detection of glutathione and glucose. Edge nitrogen active sites in the mC3N6 accommodate higher copper loading, resulting in enhanced peroxidase‐like activity and glutathione biosensing performance with a low detection limit of 0.42 ppm. It is believed that the present research will inspire the development of future‐generation nanozymes.

Selenium nanoparticles modified niobium MXene for non-enzymatic detection of glucose

Glucose sensing remains a crucial need as diabetes is a worldwide concern. This work reports the application of Nb2CTx—selenium nanoparticle composite material for the nonenzymatic sensing of glucose. The surface morphology of the synthesized composite was analyzed using various microscopic techniques like scanning electron microscopy, transmission electron microscopy, and its structural properties were analyzed using diffraction and spectroscopic methods. A gold disc electrode was modified using the nanocomposite and tested for glucose in an alkaline medium. The sensing was based on the oxidation of glucose on the catalytic surface. The glucose was quantified amperometrically at a significantly lower overpotential of 0.16 V. The sensor showed a good detection range from 2 to 30 mM with a sensitivity of 4.15 µA mM−1 cm−2 and a detection limit of 1.1 mM.

Photoexcited CuO/TiO2 Heterojunction for Photoelectrochemical Sensors for Nonenzymatic Glucose Detection.

Photoelectrochemical sensors have been studied for glucose detection because of their ability to minimize background noise and unwanted reactions. Titanium dioxide (TiO2), a highly efficient material in converting light into electricity, cannot utilize visible light. In this regard, we developed a nonenzymatic glucose sensor by using a simple one-step electrospinning technique to combine cupric oxide with TiO2 to create a heterojunction. The prepared nanofibers exhibit an extremely high aspect ratio and have a dense structure. These characteristics enhance the quantity of electron-hole pairs generated by light and the speed at which electrons are transferred. They also reduce the distance that charges need to travel and offer reactive sites for the catalytic oxidation of glucose. The sensor has a direct and proportional reaction within glucose concentration ranging from 30 μM to 2 mM under sunlight conditions. It achieves a detection limit of 9.9 μM with a signal-to-noise ratio of 3. The sensors also exhibit excellent stability, reproducibility, and selectivity. This study provides insights for development of photoelectrochemical sensors to detect glucose.

Development of a Semiquantitative Barcode Readout Approach for Paper-Based Analytical Devices (PADs) for Enzymatic H2O2 and Glucose Detection.

The integration of barcode technology with smartphones on paper-based analytical devices (PADs) presents a promising approach to bridging manual detection with digital interpretation and data storage. However, previous studies of 1D barcode approaches have been limited to providing only a "yes/no" response for analyte detection. Herein, a method of using barcode readout for semiquantitative signal detection on PADs has been achieved through the integration of barcode technology with a distance-based measurement concept on PADs. To demonstrate the feasibility of this concept, a PAD fabrication strategy incorporating barcodes was explored, using the enzymatic reaction between horseradish peroxidase (HRP), 3,3'-diaminobenzidine (DAB), and H2O2 as a model system. The enzyme-catalyzed polymerization of DAB to polyDAB in the presence of hydrogen peroxide results in the appearance of color observable by the naked eye inside a paperfluidic channel, with the color-changed length depending on the H2O2 concentration. At the same time, the barcode pattern displayed as a result of this distance-based color evolution overlaid with a paper-based barcode layer can be read using a smartphone application. Parameters affecting the signal readout performance were studied. The developed device can be used to detect H2O2 concentrations in the range of 0.25 to 10 mM within 90 min with 79.6% of barcode signals correctly readable. Additionally, results from different smartphone models showed a consistent reading performance (78.4-79.6%). Finally, the quantification of glucose levels in artificial urine samples was demonstrated. This developed PAD signaling strategy offers end-users more simplicity and can be used as a standalone device or in conjunction with other digital devices.

Effectiveness of Non-Invasive Sensor-Based Tools for Blood Glucose Detection

Effectiveness of Non-Invasive Sensor-Based Tools for Blood Glucose Detection

A colorimetric strategy and smartphone-based test strip for the detection of glucose based on the peroxidase activity of a hemin-derived nanozyme.

Nanozymes are nanomaterials with catalytic properties similar to enzymes and offer advantages over natural enzymes such as lower cost, ease of storage, and convenience for large-scale preparation. Thus, they have received increasing attention and are extensively applied in fields such as chemistry, sensing, food, environment, and medicine. Herein, a hemin-derived nanozyme (Hemin-CDs) was prepared using hemin as the precursor and used to substitute the natural horseradish peroxidase (HRP) for colorimetric detection. The prepared Hemin-CDs exhibit excellent water dispersibility, stability and superior peroxidase-like activity. They catalyze the oxidative coupling of colorless 4-aminoantipyrine (4-AAP) with N-ethyl-N-(2-hydroxy-3-sulfopropyl)-3-methylaniline sodium salt (TOOS) in the presence of H2O2, forming a purple quinone diimine dye with an absorption peak at 554 nm, which enables the quantification of H2O2 by measuring the absorbance. Quantitative detection of glucose was further demonstrated under physiological conditions. The detection of H2O2 and glucose takes only 10 minutes, with linear ranges of 1-150 μM and 2.5-300 μM, and LODs of 0.867 μM and 1.026 μM, respectively. Glucose in human serum was successfully detected with satisfactory recoveries (87.5-104.0%). Furthermore, a test strip was developed, and a smartphone was utilized to recognize the color of the test position, enabling rapid and accurate quantification of glucose concentrations within 5 minutes, which promises to enhance the accessibility and convenience of glucose testing.