The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Microneedle-Based Detection of Ketone Bodies along with Glucose and Lactate: Toward Real-Time Continuous Interstitial Fluid Monitoring of Diabetic Ketosis and Ketoacidosis
Abstract
Diabetic ketoacidosis (DKA), a severe complication of diabetes mellitus with potentially fatal consequences, is characterized by hyperglycemia and metabolic acidosis due to the accumulation of ketone bodies, which requires people with diabetes to monitor both glucose and ketone bodies. However, despite major advances in diabetes management mainly since the emergence of new-generation continuous glucose monitoring (CGM) devices capable of in vivo monitoring of glucose directly in the interstitial fluid (ISF), the continuous monitoring of ketone bodies is yet to be addressed. Here, we present the first use of a real-time continuous ketone bodies monitoring (CKM) microneedle platform. The system is based on the electrochemical monitoring of β-hydroxybutyrate (HB) as the dominant biomarker of ketone formation. Such real-time HB detection has been realized using the β-hydroxybutyrate dehydrogenase (HBD) enzymatic reaction and by addressing the major challenges associated with the stable confinement of the enzyme/cofactor couple (HBD/NAD + ) and with a stable and selective low-potential fouling-free anodic detection of NADH. The resulting CKM microneedle device displays an attractive analytical performance, with high sensitivity (with low detection limit, 50 μM), high selectivity in the presence of potential interferences, along with good stability during prolonged operation in artificial ISF. The potential applicability of this microneedle sensor toward minimally invasive monitoring of ketone bodies has been demonstrated in a phantom gel skin-mimicking model. The ability to detect HB along with glucose and lactate on a single microneedle array has been demonstrated. These findings pave the way for CKM and for the simultaneous microneedle-based monitoring of multiple diabetes-related biomarkers toward a tight glycemic control.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“ISF can be used for continuous monitoring of biomarkers, including in a recent work by Teymourian et al. [163] for continuous glucose monitoring (CGM) and continuous ketone monitoring using a microneedle sensor array.”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [163]
In the citing paper
“Moreover, they detected lactate in ISF using a similar platform and lactate oxidase enzyme.”
From The emergence of AI-based wearable sensors for digital health technology: a review (2023) · cites this paper as [163]
Citations
Cites
Wearable biosensors for healthcare monitoring
Kim, J., Campbell, A. S., de Ávila, B. E.-F., & Wang, J. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0045-y · Cited by 3,373
Self-citationAccessing analytes in biofluids for peripheral biochemical monitoring
Heikenfeld, J., Jajack, A., Feldman, B., Granger, S. W., Gaitonde, S., Begtrup, G., & Katchman, B. A. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0040-3 · Cited by 758
Tattoo-Based Noninvasive Glucose Monitoring: A Proof-of-Concept Study
Bandodkar, A. J., Jia, W., Yardımcı, C., Wang, X., Ramirez, J., & Wang, J. (2015) · Analytical Chemistry · doi:10.1021/ac504300n · Cited by 700
Self-citationRocchitta, G., Spanu, A., Babudieri, S., Latte, G., Madeddu, G., Galleri, G., Nuvoli, S. M. F., Bagella, P., Demartis, M. I., Fiore, V., et al. (2016) · Sensors · doi:10.3390/s16060780 · Cited by 584
Methods for reducing biosensor membrane biofouling
Wisniewski, N., & Reichert, M. (2000) · Colloids and Surfaces B: Biointerfaces · doi:10.1016/s0927-7765(99)00148-4 · Cited by 543
Chang, H., Zheng, M., Yu, X., Than, A., Seeni, R. Z., Kang, R., Tian, J., Duong, P. K., Liu, L., Chen, P., et al. (2017) · Advanced Materials · doi:10.1002/adma.201702243 · Cited by 465
Mechanisms of sampling interstitial fluid from skin using a microneedle patch
Samant, P. P., & Prausnitz, M. R. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1716772115 · Cited by 368
Goud, K. Y., Moonla, C., Mishra, R. K., Yu, C., Narayan, R. J., Litvan, I., & Wang, J. (2019) · ACS Sensors · doi:10.1021/acssensors.9b01127 · Cited by 358
Self-citationLipani, L., Dupont, B. G. R., Doungmene, F., Marken, F., Tyrrell, R. M., Guy, R. H., & Ilie, A. (2018) · Nature Nanotechnology · doi:10.1038/s41565-018-0112-4 · Cited by 340
Synthetic interstial fluid for isolated mammalian tissue
Bretag, A. H. (1969) · Life Sciences · doi:10.1016/0024-3205(69)90283-5 · Cited by 293
Electrocatalytic oxidation of NAD(P)H at mediator-modified electrodes
Gorton, L. G. O. (2002) · Reviews in Molecular Biotechnology · doi:10.1016/s1389-0352(01)00053-8 · Cited by 252
Room Temperature Ionic Liquids Meet Biomolecules: A Microscopic View of Structure and Dynamics
Benedetto, A., & Ballone, P. (2015) · ACS Sustainable Chemistry & Engineering · doi:10.1021/acssuschemeng.5b01385 · Cited by 176
Evaluation of a minimally invasive glucose biosensor for continuous tissue monitoring
Sharma, S., Huang, Z., Rogers, M. L., Boutelle, M. G., & Cass, A. E. G. (2016) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-016-9961-6 · Cited by 135
Guerci, B., Bénichou, M., Floriot, M., Böhme, P., Fougnot, S., Franck, P., & Drouin, P. (2003) · Diabetes Care · doi:10.2337/diacare.26.4.1137 · Cited by 128
Study of a reagentless lactate electrode
Blaedel, W. J., & Jenkins, R. A. (1976) · Analytical Chemistry · doi:10.1021/ac50002a045 · Cited by 107
Sensitive and stable amperometric measurements at ionic liquid–carbon paste microelectrodes
Musameh, M. M., & Wang, J. (2007) · Analytica Chimica Acta · doi:10.1016/j.aca.2007.11.012 · Cited by 102
Self-citationUtility of ketone measurement in the prevention, diagnosis and management of diabetic ketoacidosis
Misra, S., & Oliver, N. S. (2014) · Diabetic Medicine · doi:10.1111/dme.12604 · Cited by 98
Coimmobilization of Dehydrogenases and Their Cofactors in Electrochemical Biosensors
Zhang, M., Mullens, C. P., & Górski, W. (2007) · Analytical Chemistry · doi:10.1021/ac061698n · Cited by 94
Modified electrodes for NADH oxidation and dehydrogenase-based biosensors
Bartlett, P. N., Simon, E., & Toh, C.-S. (2002) · Bioelectrochemistry · doi:10.1016/s1567-5394(02)00047-6 · Cited by 68
Zhou, H., Zhang, Z., Yu, P., Su, L., Ohsaka, T., & Mao, L. (2010) · Langmuir · doi:10.1021/la903799n · Cited by 65
Reagentless enzyme electrodes for ethanol, lactate, and malate
Blaedel, W. J., & Engstrom, R. C. (1980) · Analytical Chemistry · doi:10.1021/ac50061a036 · Cited by 62
Teymourian, H., Salimi, A., & Hallaj, R. (2012) · Talanta · doi:10.1016/j.talanta.2012.01.003 · Cited by 59
Self-citationChristie, I., Treloar, P. H., & Vadgama, P. M. (1992) · Analytica Chimica Acta · doi:10.1016/0003-2670(92)85134-r · Cited by 54
Mascini, M., Fortunati, S., Moscone, D., Palleschi, G., Massi‐Benedetti, M., & Fabietti, P. G. (1985) · Clinical Chemistry · doi:10.1093/clinchem/31.3.451 · Cited by 53
Development of a commercial amperometric biosensor electrode for the ketone d-3-hydroxybutyrate
Forrow, N. J., Sanghera, G. S., Walters, S. J., & Watkin, J. L. (2004) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2004.07.009 · Cited by 51
Lu, X., Cheng, H., Huang, P., Yang, L., Yu, P., & Mao, L. (2013) · Analytical Chemistry · doi:10.1021/ac303743a · Cited by 49
Prevention of diabetic ketoacidosis and self-monitoring of ketone bodies: an overview
Weber, C., Kocher, S., Neeser, K., & Joshi, S. (2009) · Current Medical Research and Opinion · doi:10.1185/03007990902863105 · Cited by 40
Hedenmo, M., Narváez, A., Domı́nguez, E., & Katakis, I. (1996) · The Analyst · doi:10.1039/an9962101891 · Cited by 38
Mundaca‐Uribe, R., Moreno‐Guzmán, M., Eguílaz, M., Yáñez‐Sedeño, P., & Pingarrón, J. M. (2012) · Talanta · doi:10.1016/j.talanta.2012.07.008 · Cited by 34
Lee, K. T., Muller, D. A., Coffey, J. W., Robinson, K. J., McCarthy, J. S., Kendall, M. A. F., & Corrie, S. R. (2014) · Analytical Chemistry · doi:10.1021/ac5031682 · Cited by 34
Treloar, P. H., Christie, I., & Vadgama, P. M. (1995) · Biosensors and Bioelectronics · doi:10.1016/0956-5663(95)96806-a · Cited by 32
Khan, A. S. A., Talbot, J. A., Tieszen, K. L., Gardener, E. A., Gibson, M., & New, J. P. (2004) · Diabetic Medicine · doi:10.1111/j.1464-5491.2004.01233.x · Cited by 31
Minimal-fouling enzyme electrode for continuous flow measurement of whole blood lactate
Kyröläinen, M., Håkanson, H., Mattìasson, B., & Vadgama, P. M. (1997) · Biosensors and Bioelectronics · doi:10.1016/s0956-5663(97)00082-1 · Cited by 19
Federici, M. O., & Benedetti, M. M. (2006) · Diabetes Research and Clinical Practice · doi:10.1016/s0168-8227(06)70004-3 · Cited by 16
Laffel (1999) · doi:10.1002/(sici)1520-7560(199911/12)15:6
Flagged first, then by citations
Cited by
Sorted by citations
Electrochemical glucose sensors in diabetes management: an updated review (2010–2020)
Teymourian, H., Barfidokht, A., & Wang, J. (2020) · Chemical Society Reviews · doi:10.1039/d0cs00304b · Cited by 915
Self-citationTehrani, F., Teymourian, H., Wuerstle, B. L., Kavner, J., Patel, R., Furmidge, A., Aghavali, R., Hosseini-Toudeshki, H., Brown, C., Zhang, F., et al. (2022) · Nature Biomedical Engineering · doi:10.1038/s41551-022-00887-1 · Cited by 663
Self-citationWearable chemical sensors for biomarker discovery in the omics era
Sempionatto, J. R., Lasalde-Ramírez, J. A., Mahato, K., Wang, J., & Gao, W. (2022) · Nature Reviews Chemistry · doi:10.1038/s41570-022-00439-w · Cited by 613
Self-citationThe emergence of AI-based wearable sensors for digital health technology: a review
Shajari, S., Kuruvinashetti, K., Komeili, A., & Sundararaj, U. (2023) · Sensors · doi:10.3390/s23239498 · Cited by 535
Non-Invasive Blood Glucose Monitoring Technology: A Review
Tang, L., Chang, S. J., Chen, C.-J., & Liu, J.-T. (2020) · Sensors · doi:10.3390/s20236925 · Cited by 481
Metadata
- Authors
- Teymourian, H., Moonla, C., Tehrani, F., Vargas, E., Aghavali, R., Barfidokht, A., Tangkuaram, T., Mercier, P. P., Dassau, E., & Wang, J.
- Affiliations
- University of California San Diego (US)
- Maejo University (TH)
- Harvard University (US)
- Corresponding author
- Mercier, Patrick P.
- Dassau, Eyal
- Wang, Joseph
- ORCID
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-12-24
- Volume
- 92
- Issue
- 2
- Pages
- 2291-2300
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W2996840266
- Cited by
- 278
- References
- 35
- Citations by year
- 2026: 30 · 2025: 50 · 2024: 53 · 2023: 53 · 2022: 44 · 2021: 27 · 2020: 21
- FWCI
- 8.27
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Analytical Chemistry (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Leona M. and Harry B. Helmsley Charitable Trust (7505508-5108014 (2018PG-TI0061))
- Center for Wearable Sensors, University of California San Diego
- Topics
- Physical Sciences › Chemistry › Analytical Chemistry › Electrochemical sensors and biosensors
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Enzyme Catalysis and Immobilization
- Keywords
- ketone bodies, beta-hydroxybutyrate, diabetic ketoacidosis, diabetic ketosis, microneedle sensors, interstitial fluid, electrochemical biosensor, beta-hydroxybutyrate dehydrogenase, NADH detection, glucose monitoring, lactate monitoring, diabetes mellitus
- MeSH terms
- Glucose, Humans, Ketone Bodies, Ketosis, Needles, Time Factors, Blood Glucose Self-Monitoring, Biosensing Techniques, Diabetic Ketoacidosis, Lactic Acid, Extracellular Fluid, Electrochemical Techniques
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
