Nonenzymatic Glucose Sensor Using Bimetallic Catalysts
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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Boosting Electrochemical Catalysis and Nonenzymatic Sensing Toward Glucose by Single‐Atom Pt Supported on Cu@CuO Core–Shell Nanowires
Abstract It is critical to develop high‐performance electrocatalyst for electrochemical nonenzymatic glucose sensing. In this work, a single‐atom Pt supported on Cu@CuO core–shell nanowires (Pt 1 /Cu@CuO NWs) for electrochemical nonenzymatic glucose sensor is designed. Pt 1 /Cu@CuO NWs exhibit excellent electrocatalytic oxidation toward glucose with 70 mV lower onset potential (0.131 V) and 2.4 times higher response current than Cu NWs. Sensors fabricated using Pt 1 /Cu@CuO NWs also show high sensitivity (852.163 µA mM −1 cm −2 ), low detection limit (3.6 µM), wide linear range (0.01–5.18 µM), excellent selectivity, and great long‐term stability. The outstanding sensing performance of Pt 1 /Cu@CuO NWs, investigated by experiments and density functional theory (DFT) calculations, is attributed to the synergistic effect between Pt single atoms and Cu@CuO core–shell nanowires that generates strong binding energy of glucose on the nanowires. The work provides a new pathway for exploring highly active SACs for electrochemical nonenzymatic glucose sensor.
Chemistry↗
Engineered Glucose Oxidase‐Carbon Nanotube Conjugates for Tissue‐Translatable Glucose Nanosensors
Abstract Continuous and non‐invasive glucose monitoring and imaging is important for disease diagnosis, treatment, and management. However, glucose monitoring remains a technical challenge owing to the dearth of tissue‐transparent glucose sensors. In this study, we present the development of near‐infrared fluorescent single‐walled carbon nanotube (SWCNT) based nanosensors directly functionalized with glucose oxidase (GOx) capable of immediate and reversible glucose imaging in biological fluids and tissues. We prepared GOx‐SWCNT nanosensors by facile sonication of SWCNT with GOx in a manner that—surprisingly—does not compromise the ability of GOx to detect glucose. Importantly, we find by using denatured GOx that the fluorescence modulation of GOx‐SWCNT is not associated with the catalytic oxidation of glucose but rather triggered by glucose‐GOx binding. Leveraging the unique response mechanism of GOx‐SWCNT nanosensors, we developed catalytically inactive apo‐GOx‐SWCNT that enables both sensitive and reversible glucose imaging, exhibiting a ΔF/F 0 of up to 40 % within 1 s of exposure to glucose without consuming the glucose analyte. We finally demonstrate the potential applicability of apo‐GOx‐SWCNT in biomedical applications by glucose quantification in human plasma and glucose imaging in mouse brain slices.
Chemistry↗
Glucose assimilation rate determines the partition of flux at pyruvate between lactic acid and ethanol in Saccharomyces cerevisiae
Engineered Saccharomyces cerevisiae expressing a lactic acid dehydrogenase can metab- olize pyruvate into lactic acid. However, three pyruvate decarboxylase (PDC) isozymes drive most carbon flux toward ethanol rather than lactic acid. Deletion of endoge- nous PDCs will eliminate ethanol production, but the resulting strain suffers from C 2 auxotrophy and struggles to complete a fermentation. Engineered yeast assimilating xylose or cellobiose produce lactic acid rather than ethanol as a major product with- out the deletion of any PDC genes. We report here that sugar flux, but not sensing, contributes to the partition of flux at the pyruvate branch point in S. cerevisiae express- ing the Rhizopus oryzae lactic acid dehydrogenase (LdhA). While the membrane glucose sensors Snf3 and Rgt2 did not play any direct role in the option of predominant product, the sugar assimilation rate was strongly correlated to the partition of flux at pyruvate: fast sugar assimilation favors ethanol production while slow sugar assimilation favors lactic acid. Applying this knowledge, we created an engineered yeast capable of simultaneously converting glucose and xylose into lactic acid, increasing lactic acid production to approximately 17 g L –1 from the 12 g L –1 observed during sequential consumption of sugars. This work elucidates the carbon source-dependent effects on product selection in engineered yeast.
59 BASIC BIOLOGICAL SCIENCES↗
Data for Glucose Assimilation Rate Determines the Partition of Flux at Pyruvate Between Lactic Acid and Ethanol in Saccharomyces cerevisiae
Engineered Saccharomyces cerevisiae expressing a lactic acid dehydrogenase can metabolize pyruvate into lactic acid. However, three pyruvate decarboxylase (PDC) isozymes drive most carbon flux toward ethanol rather than lactic acid. Deletion of endogenous PDCs will eliminate ethanol production, but the resulting strain suffers from C2 auxotrophy and struggles to complete a fermentation. Engineered yeast assimilating xylose or cellobiose produce lactic acid rather than ethanol as a major product without the deletion of any PDC genes. We report here that sugar flux, but not sensing, contributes to the partition of flux at the pyruvate branch point in S. cerevisiae expressing the Rhizopus oryzae lactic acid dehydrogenase (LdhA). While the membrane glucose sensors Snf3 and Rgt2 did not play any direct role in the option of predominant product, the sugar assimilation rate was strongly correlated to the partition of flux at pyruvate: fast sugar assimilation favors ethanol production while slow sugar assimilation favors lactic acid. Applying this knowledge, we created an engineered yeast capable of simultaneously converting glucose and xylose into lactic acid, increasing lactic acid production to approximately 17 g L−1 from the 12 g L−1 observed during sequential consumption of sugars. This work elucidates the carbon source-dependent effects on product selection in engineered yeast.
Conversion↗
From small changes to big gains: pyridinium-based tetralactam macrocycle for enhanced sugar recognition in water
The complex distribution of functional groups in carbohydrates, coupled with their strong solvation in water, makes them challenging targets for synthetic receptors. Despite extensive research into various molecular frameworks, most synthetic carbohydrate receptors have exhibited low affinities, and their interactions with sugars in aqueous environments remain poorly understood. In this work, we present a simple pyridinium-based hydrogen-bonding receptor derived from a subtle structural modification of a well-known tetralactam macrocycle. This small structural change resulted in a dramatic enhancement of glucose binding affinity, increasing from 56 M −1 to 3001 M −1 . Remarkably, the performance of our synthetic lectin surpasses that of the natural lectin, concanavalin A, by over fivefold. X-ray crystallography of the macrocycle–glucose complex reveals a distinctive hydrogen bonding pattern, which allows for a larger surface overlap between the receptor and glucose, contributing to the enhanced affinity. Furthermore, this receptor possesses allosteric binding sites, which involve chloride binding and trigger receptor aggregation. This unique allosteric process reveals the critical role of structural flexibility in this hydrogen-bonding receptor for the effective recognition of sugars. We also demonstrate the potential of this synthetic lectin as a highly sensitive glucose sensor in aqueous solutions.
Zhai, Canjia↗
Tailoring the d-band center on Ru 1 Cu single-atom alloy nanotubes for boosting electrochemical non-enzymatic glucose sensing
The development of cost-effective and highly efficient electrocatalysts is critical to help electrochemical non-enzymatic sensors achieve high performance. Here, in this work, a new class of catalyst, Ru single atoms confined on Cu nanotubes as a single-atom alloy (Ru 1 Cu NTs), with a unique electronic structure and property, was developed to construct a novel electrochemical non-enzymatic glucose sensor for the first time. The Ru 1 Cu NTs with a diameter of about 24.0 nm showed a much lower oxidation potential (0.38 V) and 9.0-fold higher response (66.5 μA) current than Cu nanowires (Cu NWs, oxidation potential 0.47 V and current 7.4 μA) for glucose electrocatalysis. Moreover, as an electrochemical non-enzymatic glucose sensor, Ru1Cu NTs not only exhibited twofold higher sensitivity (54.9 μA mM −1 cm −2 ) and wider linear range (0.5–8 mM) than Cu NWs, but also showed a low detection limit (5.0 μM), excellent selectivity, and great stability. According to theoretical calculation results, the outstanding catalytic and sensing performance of Ru 1 Cu NTs could be ascribed to the upshift of the d-band center that helped promote glucose adsorption. This work presents a new avenue for developing highly active catalysts for electrochemical non-enzymatic sensors.
electrochemistry↗
Oxide derived Cu nanofibril assembly for enhanced nonenzymatic glucose sensing
In this report, we have prepared copper nanofibril assembly via thermal oxidation followed by electrochemical reduction processes, exhibiting superior glucose detection ability. The morphological analysis evidenced the formation of rough islands or nanofibril structure on the Cu surface depending on initial thermal oxidation temperature. The glucose detection performance was investigated by performing cyclic voltammetry and chronoamperometry with varying glucose concentration. A high sensitivity (4131.57 μA mM – 1 cm – 2 ), low detection limit (1.41 μM), wider linear range (0–3.9 mM) and long–term stability (30 days) have been recorded for electrode thermally oxidized at 400 °C followed by electrochemical reduction process (rCu_400). The sensitivity is almost three times higher in comparison to the planner Cu surface. This significantly enhanced glucose sensing ability rCu_400 has been attributed to the nanofibril morphology, origination of Cu (111) facet and formation of a stable oxide layer evidenced by scanning electron microscopy, X-ray diffraction and energy dispersive spectroscopy analysis. Despite higher sensitivity, rCu_400 electrode does not show any response to the chloride ion, dopamine, ascorbic acid and uric acid. Finally, these results indicate that the Cu nanofibril structure prepared via simple oxidation/reduction process can be an excellent candidate to be used as an electrode for glucose sensing application.
36 MATERIALS SCIENCE↗
Nanopore device for reversible ion and molecule sensing or migration
Disclosed are methods and devices for detection of ion migration and binding, utilizing a nanopipette adapted for use in an electrochemical sensing circuit. The nanopipette may be functionalized on its interior bore with metal chelators for binding and sensing metal ions or other specific binding molecules such as boronic acid for binding and sensing glucose. Such a functionalized nanopipette is comprised in an electrical sensor that detects when the nanopipette selectively and reversibly binds ions or small molecules. Also disclosed is a nanoreactor, comprising a nanopipette, for controlling precipitation in aqueous solutions by voltage-directed ion migration, wherein ions may be directed out of the interior bore by a repulsing charge in the bore.
47 OTHER INSTRUMENTATION↗
Light-triggered electrochemical biosensor using singlet oxygen for self-powered operation and glucose detection
This study introduces a light-activated sensing strategy that integrates photosensitization with electrochemical detection. The sensor employs Eosin Y, a photosensitizer that generates singlet oxygen ( 1 O 2 ) via type II photosensitization. Immobilized within a thin polymer matrix on a carbon working electrode, Eosin Y produces 1 O 2 , under green light (520 nm) illumination, initiating a redox process that yields a measurable current. To incorporate biosensing capabilities and enable self-powered operation, this 1 O 2 – mediated process was coupled with glucose oxidase (GOx) to construct a fully operational glucose biosensor. The addition of glucose reverses the current flow by causing GOx to compete for electrons, with the resulting current magnitude correlating with glucose concentration providing a sensitive measure of glucose. The biosensor, as proof-of-principle, demonstrated excellent performance over a range of glucose concentrations (0–73 mM), achieving a detection limit (LOD) of 2.8 mM for steady state photocurrent under oxygen-saturated conditions. This platform leverages light and 1 O 2 as stimuli for tunable, on-demand signal control, offering a novel approach for adaptive, real-time biosensing technologies.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Functional Data Analysis in Wearable Body Sensor Networks
Improving response time of indirect room-size calorimeters is still an outstanding problem in metabolic research. Accurate estimates of instantaneous rates of gaseous exchange require numerical differentiation of measured gaseousgas concentrations. We propose a new method to estimate the instantaneous gaseousgas exchange rates in indirect calorimetry. In contrast to the previously developed techniques, the method addresses the problem of differentiation of gaseous concentrations as an ill-posed problem. By applying the method of regularization, the problem of differentiation is converted into a well-posed problem resulting in smooth and consistent gaseous exchange rates. The validity of the method is tested on a large dataset of calorimeter experiments which included 313 human experiments along with 231 alcohol combustion experiments. It is demonstrated that the method is able to reliably differentiate between the “unphysiological” process of alcohol combustion and physiological variations produced by human metabolism. The method also allowed unraveling the previously unreported relative kinetics of O2 consumption and Respiratory Quotient (RQ) in humans. It was found that the kinetics of oxidative fuel selection lags behind the energy expenditure in humans exhibiting some sort of oxidative inertia. The time lag varies from 2-3 min up to 30 min, depending on particular individual. No such lag was found in alcohol combustion experiments. In addition to the relative kinetics of substrate oxidation, two statistical indexes reflecting variability of minute-by-minute RQ were estimated. The indexes were the RQ’s standard deviation and RQ’s first-order derivative. Both indexes showed statistically significant difference between human experiments and alcohol combustion experiments. We conclude that the proposed method can consistently extract physiologically-relevant information from noisy calorimetry data and the aforesaid information can provide additional insights into the mechanism of metabolic fuel selection in humans.
54 ENVIRONMENTAL SCIENCES↗
Functional Data Analysis in Wearable Body Sensor Networks
Improving response time of indirect room-size calorimeters is still an outstanding problem in metabolic research. Accurate estimates of instantaneous rates of gaseous exchange require numerical differentiation of measured gaseousgas concentrations. We propose a new method to estimate the instantaneous gaseousgas exchange rates in indirect calorimetry. In contrast to the previously developed techniques, the method addresses the problem of differentiation of gaseous concentrations as an ill-posed problem. By applying the method of regularization, the problem of differentiation is converted into a well-posed problem resulting in smooth and consistent gaseous exchange rates. The validity of the method is tested on a large dataset of calorimeter experiments which included 313 human experiments along with 231 alcohol combustion experiments. It is demonstrated that the method is able to reliably differentiate between the “unphysiological” process of alcohol combustion and physiological variations produced by human metabolism. The method also allowed unraveling the previously unreported relative kinetics of O2 consumption and Respiratory Quotient (RQ) in humans. It was found that the kinetics of oxidative fuel selection lags behind the energy expenditure in humans exhibiting some sort of oxidative inertia. The time lag varies from 2-3 min up to 30 min, depending on particular individual. No such lag was found in alcohol combustion experiments. In addition to the relative kinetics of substrate oxidation, two statistical indexes reflecting variability of minute-by-minute RQ were estimated. The indexes were the RQ’s standard deviation and RQ’s first-order derivative. Both indexes showed statistically significant difference between human experiments and alcohol combustion experiments. We conclude that the proposed method can consistently extract physiologically-relevant information from noisy calorimetry data and the aforesaid information can provide additional insights into the mechanism of metabolic fuel selection in humans.
60 - APPLIED LIFE SCIENCES↗
Manganese Carbonate/Laser-Induced Graphene Composite for Glucose Sensing
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗