Salivary glucose sensing using highly sensitive and selective non-enzymatic porous NiO nanostructured electrodes

Chakraborty, Pinak; Deka, Nitumoni; Patra, Dulal Chandra; Debnath, Kamalesh; Mondal, Sankar Prasad

doi:10.1016/j.surfin.2021.101324

Cited by 26 publications

(13 citation statements)

References 52 publications

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“…However, Amer et al [ 33 ] found no salivary glucose of the control group. We found that the saliva glucose levels of DM patients obtained by the six saliva collection methods were higher than in the control group, and the difference was statistically significant, which was consistent with the conclusions of most other studies [ 23 , 24 ]. Similar to our study, Mishra et al [ 34 ] found a positive and statistically significant correlation between salivary and blood glucose in DM patients.…”

Section: Discussionsupporting

confidence: 91%

“…Although the biomarkers in saliva reflect the health status of the human body, the use of salivary glucose as a diagnostic fluid for DM has been hindered, mainly because the correlation between salivary glucose and blood glucose has been greatly controversial [ 22 ]. Studies have shown that for DM patients, the salivary glucose level is positively correlated with the blood glucose level, so salivary glucose can be used as a marker for DM detection [ 23 , 24 ]. However, in different studies, the relationship between salivary glucose and blood glucose is quite different with completely opposite conclusions, pointing out that salivary glucose and blood glucose have no significant correlation [ 25 , 26 ].…”

Section: Introductionmentioning

confidence: 99%

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Correlations of Salivary and Blood Glucose Levels among Six Saliva Collection Methods

Cui

Zhang

Zhu

et al. 2022

IJERPH

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Background: Saliva has been studied as a better indicator of disorders and diseases than blood. Specifically, the salivary glucose level is considered to be an indicator of diabetes mellitus (DM). However, saliva collection methods can affect the salivary glucose level, thereby affecting the correlation between salivary glucose and blood glucose. Therefore, this study aims to identify an ideal saliva collection method and to use this method to determine the population and individual correlations between salivary glucose and blood glucose levels in DM patients and healthy controls. Finally, an analysis of the stability of the individual correlations is conducted. Methods: This study included 40 age-matched DM patients and 40 healthy controls. In the fasting state, saliva was collected using six saliva collection methods, venous blood was collected simultaneously from each study participant, and both samples were analyzed at the same time using glucose oxidase peroxidase. A total of 20 DM patients and 20 healthy controls were arbitrarily selected from the above participants for one week of daily testing. The correlations between salivary glucose and blood glucose before and after breakfast were analyzed. Finally, 10 DM patients and 10 healthy controls were arbitrarily selected for one month of daily testing to analyze the stability of individual correlations. Results: Salivary glucose levels were higher in DM patients than healthy controls for the six saliva collection methods. Compared with unstimulated saliva, stimulated saliva had decreased glucose level and increased salivary flow. In addition, unstimulated parotid salivary glucose was most correlated with blood glucose level (R2 = 0.9153), and the ROC curve area was 0.9316, which could accurately distinguish DM patients. Finally, it was found that the correlations between salivary glucose and blood glucose in different DM patients were quite different. The average correlation before breakfast was 0.83, and the average correlation after breakfast was 0.77. The coefficient of variation of the correlation coefficient before breakfast within 1 month was less than 5%. Conclusion: Unstimulated parotid salivary glucose level is the highest and is most correlated with blood glucose level, which can be accurately used to distinguish DM patients. Meanwhile, the correlation between salivary glucose and blood glucose was found to be relatively high and stable before breakfast. In general, the unstimulated parotid salivary glucose before breakfast presents an ideal saliva collecting method with which to replace blood-glucose use to detect DM, which provides a reference for the prediction of DM.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Correlations of Salivary and Blood Glucose Levels among Six Saliva Collection Methods

Cui

Zhang

Zhu

et al. 2022

IJERPH

View full text Add to dashboard Cite

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“…Human salivary glucose levels are about 0.008–1.77 mM ( Tseng et al, 2021 ). Because the level of glucose concentration in saliva is only 1%–10% of the glucose concentration level in the blood, its detection equipment needs to have extremely high sensitivity ( Wei et al, 2021 ; Chakraborty P et al, 2021a ). Ezhil Vilian et al (2021) fabricated the Ni 2 CoS 4 nanomaterials on carbon nanofibers by electrospinning and hydrothermal route to measure the glucose in saliva ( Figure 2B ).…”

Section: Background Knowledge For Glucose Sensorsmentioning

confidence: 99%

“…Tears are an emerging body fluid used for medical monitoring ( Tam et al, 2021 ). The sweat and saliva blood glucose monitoring problems include the sample collection methods, sample contamination (skin dust and oral wounds), and bias caused by skin exposure different environments, oral drugs, and proteolytic enzymes ( Chakraborty P et al, 2021a ). Tears usually contain more than 20 different substances, including water, electrolytes, proteins, metabolites (e.g., glucose), and trace metals.…”

Section: Background Knowledge For Glucose Sensorsmentioning

confidence: 99%

“…The use of polymers as the substrate of the nanofibers ensures the immobilization efficiency of the enzyme and also has various other functions, such as catalysis and electrical conductivity ( Chansaenpak et al, 2021 ; Naresh and Lee, 2021 ). The polymers in electrospun can be divided into the following categories: natural polymer, synthetic polymer, conductive polymer, and molecular imprinted polymer ( Chakraborty et al, 2021a ; Kim et al, 2019a ). Most of the functional ingredients in electrospun nanofiber membranes are nanomaterials, which can serve both as substrates of enzymes and reaction mediators to improve the detection signal ( Chakraborty S et al, 2021 ; Yang et al, 2020 ).…”

Section: Materials For Nanofiber-based Glucose Sensorsmentioning

confidence: 99%

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Electrospun nanofiber-based glucose sensors for glucose detection

Zhang

Liu

et al. 2022

Front. Chem.

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Diabetes is a chronic, systemic metabolic disease that leads to multiple complications, even death. Meanwhile, the number of people with diabetes worldwide is increasing year by year. Sensors play an important role in the development of biomedical devices. The development of efficient, stable, and inexpensive glucose sensors for the continuous monitoring of blood glucose levels has received widespread attention because they can provide reliable data for diabetes prevention and diagnosis. Electrospun nanofibers are new kinds of functional nanocomposites that show incredible capabilities for high-level biosensing. This article reviews glucose sensors based on electrospun nanofibers. The principles of the glucose sensor, the types of glucose measurement, and the glucose detection methods are briefly discussed. The principle of electrospinning and its applications and advantages in glucose sensors are then introduced. This article provides a comprehensive summary of the applications and advantages of polymers and nanomaterials in electrospun nanofiber-based glucose sensors. The relevant applications and comparisons of enzymatic and non-enzymatic nanofiber-based glucose sensors are discussed in detail. The main advantages and disadvantages of glucose sensors based on electrospun nanofibers are evaluated, and some solutions are proposed. Finally, potential commercial development and improved methods for glucose sensors based on electrospinning nanofibers are discussed.

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Glucose Sensing in Saliva

Giaretta,

Zulli,

Prabhakar

et al. 2024

Advanced Sensor Research

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Glucose plays critical roles in many human body functions, above all as a source of energy. Abnormal levels of glucose are correlated to different diseases, importantly including diabetes. As such, quantification of glucose levels in body fluids is essential for health monitoring. Blood tests and, more recently, portable interstitial fluid tests, currently represent the benchmarks for glucose detection. Inconvenient invasive methods such as blood tests pose burdens on both patients and the healthcare system. In this review, noninvasive approaches to measure glucose levels in the human body are discussed, utilizing saliva as an alternative to conventional blood samples. Techniques explored and with the potential to enhance accuracy and their associated challenges are discussed.

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Salivary glucose sensing using highly sensitive and selective non-enzymatic porous NiO nanostructured electrodes

Cited by 26 publications

References 52 publications

Correlations of Salivary and Blood Glucose Levels among Six Saliva Collection Methods

Correlations of Salivary and Blood Glucose Levels among Six Saliva Collection Methods

Electrospun nanofiber-based glucose sensors for glucose detection

Glucose Sensing in Saliva

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