Paper microfluidic device using carbon dots to detect glucose and lactate in saliva samples

Rossini, Eduardo Luiz; Milani, Maria Izabel; Lima, Liliane Spazzapam; Pezza, Helena Redigolo

doi:10.1016/j.saa.2020.119285

Cited by 38 publications

(18 citation statements)

References 55 publications

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“…COVID-19 positivity did change the correlation maps between the two bio uids, but from a less correlated starting point than sebum / serum, and resulting in weaker diagnostic power overall. As a ltrate, saliva should be in uenced by serum levels, but concentrations are lower than in blood 30 . Furthermore, the salivary biome is independent and has its own discrete functions and is markedly more subject to direct contamination from food or medication.…”

Section: Discussionmentioning

confidence: 99%

An Integrated Analysis and Comparison of Serum, Saliva and Sebum for COVID-19 Metabolomics

Spick

Bailey

Lewis

et al. 2022

Preprint

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Non-invasive sampling approaches are desirable in healthcare settings due to the lower burden on patients and clinical staff. In the field of metabolomics, however, most studies have utilised blood serum or plasma. In this work 83 COVID-19 positive and negative hospitalised participants provided serum, saliva and sebum samples for analysis by mass spectrometry. Here we present the first comprehensive analysis of correlations between serum metabolites, salivary metabolites and sebum lipids, and consider their relative accuracy in differentiating COVID-19 positive participants from controls. Sebum lipids showed clear correlations to serum metabolites, with widespread changes to the serum-sebum lipid axis in COVID-19 positive participants, evidence of multi-organ dyslipidemia. In the COVID-19 positive cohort, correlations were notably marked between sebum lipids and the immunostimulatory hormone dehydroepiandrosterone sulphate. In terms of diagnostic accuracy, serum performed best by multivariate analysis (sensitivity and specificity of 0.97), with the dominant changes in triglyceride and bile acid levels, concordant with other studies identifying dyslipidemia as a hallmark of COVID-19 infection. Sebum diagnostic accuracy performed well (sensitivity 0.92; specificity 0.84), with saliva offering weaker diagnostic accuracy (sensitivity 0.78; specificity 0.83). These findings highlight the potential for integrated biofluid analyses to provide insight into the whole-body atlas of pathophysiological conditions.

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Section: Discussionmentioning

confidence: 99%

An Integrated Analysis and Comparison of Serum, Saliva and Sebum for COVID-19 Metabolomics

Spick

Bailey

Lewis

et al. 2022

Preprint

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“…No pathways met the criteria for both meaningful impact and statistical significance, possibly due to the number features identified in each pathway being notably smaller than typically achieved in serum or plasma, consistent with saliva being a filtrate and in general featuring lower metabolic concentrations. 28 High Low . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.…”

Section: Analysis Of Cohorts By Multivariate Techniquesmentioning

confidence: 99%

Section: Analysis Of Cohorts By Multivariate Techniquesmentioning

confidence: 99%

Untargeted saliva metabolomics reveals COVID-19 severity

Frampas

Longman

Spick

et al. 2021

Preprint

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Background The COVID-19 pandemic is likely to represent an ongoing global health issue given the potential for vaccine escape and the low likelihood of eliminating all reservoirs of the disease. Whilst diagnostic testing has progressed at pace, there is an unmet clinical need to develop tests that are prognostic, to triage the high volumes of patients arriving in hospital settings. Recent research has shown that serum metabolomics has potential for prognosis of disease progression. 1 In a hospital setting, collection of saliva samples is more convenient for both staff and patients, and therefore offers an alternative sampling matrix to serum. We demonstrate here for the first time that saliva metabolomics can reveal COVID-19 severity. Methods 88 saliva samples were collected from hospitalised patients with clinical suspicion of COVID-19, alongside clinical metadata. COVID-19 diagnosis was confirmed using RT-PCR testing. COVID severity was classified using clinical descriptors first proposed by SR Knight et al. Metabolites were extracted from saliva samples and analysed using liquid chromatography mass spectrometry. Results In this work, positive percent agreement of 1.00 between a PLS-DA metabolomics model and the clinical diagnosis of COVID severity was achieved. The negative percent agreement with the clinical severity diagnosis was also 1.00, for overall percent agreement of 1.00. Conclusions This research demonstrates that liquid chromatography-mass spectrometry can identify salivary biomarkers capable of separating high severity COVID-19 patients from low severity COVID-19 patients in a small cohort study.

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“…However, one of their areas of opportunity is the limit of detection, which may prevent their application in non-conventional fluids. To overcome this challenge, other detection approaches have been analyzed, such as detection by electrochemical methods [ 114 , 115 ], distance-based [ 83 , 116 ], luminescence [ 79 , 117 ], fluorescence [ 79 , 118 ], calorimetry [ 119 , 120 ], and mass spectra [ 121 , 122 ]. Most of the paper-based POCs reported in Table 1 of this review have reported stability under refrigeration (4 °C) [ 4 , 69 , 73 , 76 , 79 , 80 , 84 , 123 ].…”

Section: Paper-based Point-of-care Platforms For Screening and Monitoring Of Type 2 Diabetes Mellitusmentioning

confidence: 99%

Current Challenges and Future Trends of Enzymatic Paper-Based Point-of-Care Testing for Diabetes Mellitus Type 2

2021

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A point-of-care (POC) can be defined as an in vitro diagnostic test that can provide results within minutes. It has gained enormous attention as a promising tool for biomarkers detection and diagnosis, as well as for screening of chronic noncommunicable diseases such as diabetes mellitus. Diabetes mellitus type 2 is one of the metabolic disorders that has grown exponentially in recent years, becoming one of the greatest challenges to health systems. Early detection and accurate diagnosis of this disorder are essential to provide adequate treatments. However, efforts to reduce incidence should remain not only in these stages but in developing continuous monitoring strategies. Diabetes-monitoring tools must be accessible and affordable; thus, POC platforms are attractive, especially paper-based ones. Paper-based POCs are simple and portable, can use different matrixes, do not require highly trained staff, and are less expensive than other platforms. These advantages enhance the viability of its application in low-income countries and hard-to-reach zones. This review aims to present a critical summary of the main components required to create a sensitive and affordable enzymatic paper-based POC, as well as an oriented analysis to highlight the main limitations and challenges of current POC devices for diabetes type 2 monitoring and future research opportunities in the field.

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Paper microfluidic device using carbon dots to detect glucose and lactate in saliva samples

Cited by 38 publications

References 55 publications

An Integrated Analysis and Comparison of Serum, Saliva and Sebum for COVID-19 Metabolomics

An Integrated Analysis and Comparison of Serum, Saliva and Sebum for COVID-19 Metabolomics

Untargeted saliva metabolomics reveals COVID-19 severity

Current Challenges and Future Trends of Enzymatic Paper-Based Point-of-Care Testing for Diabetes Mellitus Type 2

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