Magnetite as a platform material in the detection of glucose, ethanol and cholesterol

Jaime, J.; Rangel, Gerardo Farías; Muñoz‐Bonilla, Alexandra; Mayoral, Álvaro; Herrasti, P.

doi:10.1016/j.snb.2016.07.059

Cited by 27 publications

(14 citation statements)

References 41 publications

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“…Palladium-cobalt nanoparticles over carbon nanotubes using one-pot synthesis method was reported by Huang et al as shown in Figure 3F [93]. [82] Copyright © 2017 Elsevier, (B) molybdenum disulphide (MoS2) nanosheets [91] Copyright © 2017 Elsevier, (C) enzyme modified screen printed electrodes [92] Copyright © 2017 Elsevier, (D) carbon black-carbon nanotubes [82], (E) magnetite nanoparticles/polydopamine [89] Copyright © 2017 Elsevier, (F) Palladium-cobalt nanoparticles/ carbon nanotubes [93] Copyright © 2017 Elsevier.…”

Section: Electrochemical Detection Strategies For Multi-analyte Detecmentioning

confidence: 95%

“…A multi-analyte sensor for the detection of seven analytes namely, H 2 O 2 , lactate, NADH (reduced nicotinamide adenine dinucleotide), ascorbic acid, uric acid, nitrite and dopamine was fabricated with a hybrid interface of iron oxide nanoparticles and reduced graphene oxide nanosheets on an indium tin oxide electrode [88]. While the role of H 2 O 2 , lactate, ascorbic acid, uric acid and dopamine in MetS-related disorders have already been identified, NADH being a key co-enzyme in glucose and lipid metabolic pathways are important indicators of the metabolic regulation in an individual [89]. Similarly, it has been demonstrated that reduced nitrite and nitrate levels contribute to endothelial dysfunction and MetS [90].…”

Section: Electrochemical Detection Strategies For Multi-analyte Detecmentioning

confidence: 99%

“…2 µM and 2.2 mM, uric acid levels in the range4-20 µM, ascorbic acid in the sample between 160 µM and 7.2 mM, dopamine concentrations of0.4-3.5 µM, H 2 O 2 concentrations between 20 nM and 0.28 µM, nitrite and NADH levels in the range 20-210 µM and 2-15 µM respectively [88]. Magnetite nanoparticles coated with polydopamine were covalently attached to glucose oxidase as shown in Figure 3E was employed for the analysis of glucose in human serum samples [89].In another interesting work, molybdenum disulphide (MoS2) nanosheets supported Au-Pd bimetallic nanoparticles were employed for the enzyme-free sensing of glucose and H 2 O 2 as indicated in Figure 3B. This non-enzymatic sensor exhibited a wide linear range of 0.8 µM-10 mM for H 2 O 2 and 0.5-20 mM for glucose [91].…”

Section: Electrochemical Detection Strategies For Multi-analyte Detecmentioning

confidence: 99%

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Metabolic Syndrome—An Emerging Constellation of Risk Factors: Electrochemical Detection Strategies

Madhurantakam

Devi

Babu

et al. 2019

Sensors

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Metabolic syndrome is a condition that results from dysfunction of different metabolic pathways leading to increased risk of disorders such as hyperglycemia, atherosclerosis, cardiovascular diseases, cancer, neurodegenerative disorders etc. As this condition cannot be diagnosed based on a single marker, multiple markers need to be detected and quantified to assess the risk facing an individual of metabolic syndrome. In this context, chemical- and bio-sensors capable of detecting multiple analytes may provide an appropriate diagnostic strategy. Research in this field has resulted in the evolution of sensors from the first generation to a fourth generation of ‘smart’ sensors. A shift in the sensing paradigm involving the sensing element and transduction strategy has also resulted in remarkable advancements in biomedical diagnostics particularly in terms of higher sensitivity and selectivity towards analyte molecule and rapid response time. This review encapsulates the significant advancements reported so far in the field of sensors developed for biomarkers of metabolic syndrome.

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Section: Electrochemical Detection Strategies For Multi-analyte Detecmentioning

confidence: 95%

Section: Electrochemical Detection Strategies For Multi-analyte Detecmentioning

confidence: 99%

Section: Electrochemical Detection Strategies For Multi-analyte Detecmentioning

confidence: 99%

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Metabolic Syndrome—An Emerging Constellation of Risk Factors: Electrochemical Detection Strategies

Madhurantakam

Devi

Babu

et al. 2019

Sensors

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“…Detection of cholesterol concentrations has been carried out by many researchers such as, Magnetite as a platform material for detecting glucose, ethanol and cholesterol [8]. Amperometric detection of cholesterol uses cobalt (II) chloride as an electrocatalyst in aprotic media [9].…”

Section: Introductionmentioning

confidence: 99%

Efficiency of Optical Sensors with Quasi Gaussian Beam for Determining Cholesterol Concentration

Budiyanto¹,

Suhariningsih²,

Yasin³

2018

Proceedings of the International Conference on Science and Technology (ICST 2018)

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Research on fiber optic sensors with Quasi Gaussian beam has been carried out aiming to analyze the beam intensity profile of the light beam, sensor performance and sensor sensitivity to determine cholesterol concentration. The concept of laser beam propagation is guided by an optical fiber bundle in a solution with a cholesterol concentration that varies from 0 to 300 ppm. The detection mechanism of cholesterol concentration is the propagation of the He-Ne laser beam with a wavelength of 632.5 nm through the fiber optic bundle to the cholesterol solution, then reflected using a flat mirror. Reflective waves enter optical fibers through fiber receiving. This signal is captured by a silicon detector (SL-818, Newport) in the form of electrical voltage. The results show that the power profile increases with increasing distance of object shift from optical fiber. After reaching peak output power, the power profil will decrease exponentially with increasing distance. The performance of the shift sensor of the Quasi Gaussian beam optical fiber to determine the concentration of cholesterol achieves high sensitivity, linearity and accuracy with a sensitivity value of 0.08 mV / ppm, linearity of more than 97%, linear range of 0-300 ppm, resolution of 1.76 ppm and standard deviation of 0.14 mV. Sensitivity through mathematical analysis using the Quasi Gaussian beam approach is higher than the sensitivity of the Gaussian beam. Based on the output power profile, sensor performance, sensitivity through the flat mirror reflection field and sensor stability, it can be concluded that the optical fiber sensor using Quasi Gaussian beam can determine cholesterol concentration.

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“…, álcool oxidase[100][101][102][103] e álcool catalase 100. Diversos materiais também foram preparados com o intuito de evitar o uso de componentes biológicos, como nanopartículas de paládio e óxido de zinco,104 nanofios de níquel,105,106 nanoflores de platina e rutênio 107 entre outros 108,.…”

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Preparação e caracterização do nanocompósito baseado em óxido de grafeno reduzido/hexacianoferrato de óxido de rutênio e aplicação como sensor eletroquímico

Borges¹

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The preparation of a nanocomposite based on reduced graphene oxide and ruthenium oxide hexacyanoferrate (rGO/RuOHCF) nanoparticles was performed by cyclic voltammetry. Control-materials were prepared analogously for comparison. Electrochemical tests revealed a synergic effect between the rGO sheets and RuOHCF nanoparticles due to current intensity increasing and higher stability during 50 voltammetric scans comparing to RuOHCF film. The results were more pronounced in acidic media (pH= 1.5), which was used for the rest of the work. Raman and infrared spectroscopy were performed and revealed the effective reduction of GO and the hexacyanoferrate formation. The scanning electron microscopy (SEM) showed RuOHCF nanoparticles of approximately 89 nm distributed over rGO sheets and the expected elements were identified by energy dispersive X-ray spectroscopy (EDS). The electrochemical oxidation processes of ranitidine (RTD) and ethanol (EtOH) were analyzed using the rGO/RuOHCF electrode. The scan rate tests revealed that ranitidine's electroxidation is controlled by adsorption and EtOH's by diffusion. The standard analytes were used to voltammetric determination and showed high linear correlation (R 2 = 0.999) in a concentration range of 20 to 150 µmol L-1 for ranitidine and 2.5 to 150 mmol L-1 for ethanol. The amperometric determination coupled to batch-injection analysis (BIA) provided the determination of those molecule in commercial samples. RTD was successfully detected (95.8 and 95.5%) in two different brand of medicines, and EtOH was recovered in 104.4% in commercial alcohol sample and 101.8% in cachaça sample. Thereby, the rGO/RuOHCF nanocomposite synthesized exclusively by an electrochemical route showed a promising electroanalytical sensor for different molecules.

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Magnetite as a platform material in the detection of glucose, ethanol and cholesterol

Cited by 27 publications

References 41 publications

Metabolic Syndrome—An Emerging Constellation of Risk Factors: Electrochemical Detection Strategies

Metabolic Syndrome—An Emerging Constellation of Risk Factors: Electrochemical Detection Strategies

Efficiency of Optical Sensors with Quasi Gaussian Beam for Determining Cholesterol Concentration

Preparação e caracterização do nanocompósito baseado em óxido de grafeno reduzido/hexacianoferrato de óxido de rutênio e aplicação como sensor eletroquímico

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