Trends in Nanomaterial-Based Non-Invasive Diabetes Sensing Technologies
Abstract
:1. Introduction
2. Blood-Based Diagnostics (The Gold Standard)
3. Urine-Based Diagnostics
4. Saliva-Based Diagnostics
5. Sweat-Based Diagnostics
6. Tear-Based Diagnostics
7. Breath-Based Diagnostics
- Variation in acetone concentration in the general public
- Measured on empty stomach or after meal
- Nature and amount of food taken [107]
- Breathing maneuvers alveolar vs. non-alveolar during sample collection [108]
- Percentage of moisture in the breath
- Before/after smoking
- Presence of other disease conditions in patients (COPD, hypercapnia)
- Exercise, sports, etc.
- Significant acetone is produced only during extreme case of ketoacidosis.
8. Conclusion and Future Work
Medium | Biomarkers | Typical Concentrations | Most Studied Materials |
---|---|---|---|
Blood | Glucose | 2–30 mM [39] | ZnO [8,9,10]
Metal NP [11,12,13,14] Metal oxide [112] CNT [16,17,19,20] |
Urine | Glucose | 2.78–5.5 mM [25] | Metal NP [113]
Pt [26,114] CNT [28,29,115,116] |
Saliva | Glucose | 0.008–0.21 mM [38] | Polymer [40,41,46]
Quantum dots [43,117] CNT [42,44,45] Graphene [118] |
Sweat | Glucose | 0.277–1.11 mM [49] | Polymer [59]
CNT [56,119] |
Tears | Glucose | 0.1–0.6 mM [71] | Polymer [71,120]
Graphene [76] Metal/metal oxide NP [121] |
Breath | Acetone | 21–0.5 ppm [93] | Polymer [95]
Metal oxide [98,99,101] CNT [96,102,104] |
Media | Advantages | Disadvantages |
---|---|---|
Blood | Well-established analytical technique
Low-cost instrumentation Continuous and reliable procedure | Invasive
Highly uncomfortable for patients Infection risk from bruised skin |
Urine | Non-invasive and painless
Affordability Portable Rapid reproduction | Low accuracy
Low glucose concentration levels Frequent calibration Susceptible to interference by bodily fluid volume to concentration ratio |
Saliva | Non-invasive and painless
Safe for children and adults Easy sample collection Cost-effective | Low concentration levels
Requires high sensitivity and selectiveness to provide significant results Lag in saliva glucose, may not suitable for type I diabetes |
Sweat | Easy sample collection
Non-/minimally invasive Sufficient quantities and rapid reproduction | High calibration times
Irritation and blistering of skin Inaccurate readings Lag and inconsistent testing Low glucose concentration levels |
Tears | Highly accessible
Less susceptibility to dilution Numerous testing methods Cost effective Continuously replenished | Poor correlation with blood glucose level
Requires low detection limit and high sensitivity and selectivity Interference from high lactate levels and variable pH levels Lack of a suitable power source for testing |
Breath | Non-invasive and painless Quick results Ease of use | Results and analysis influenced by multiple confounding factors
Bio-markers are not very well defined |
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Makaram, P.; Owens, D.; Aceros, J. Trends in Nanomaterial-Based Non-Invasive Diabetes Sensing Technologies. Diagnostics 2014, 4, 27-46. https://doi.org/10.3390/diagnostics4020027
Makaram P, Owens D, Aceros J. Trends in Nanomaterial-Based Non-Invasive Diabetes Sensing Technologies. Diagnostics. 2014; 4(2):27-46. https://doi.org/10.3390/diagnostics4020027
Chicago/Turabian StyleMakaram, Prashanth, Dawn Owens, and Juan Aceros. 2014. "Trends in Nanomaterial-Based Non-Invasive Diabetes Sensing Technologies" Diagnostics 4, no. 2: 27-46. https://doi.org/10.3390/diagnostics4020027