What Is Left for Real-Life Lactate Monitoring? Current Advances in Electrochemical Lactate (Bio)Sensors for Agrifood and Biomedical Applications
Abstract
1. Introduction
2. Electrochemical (Bio)Sensor Transduction Approaches
2.1. Amperometric Lactate Biosensors
2.2. Potentiometric and Conductometric Lactate Biosensors
2.3. Enzyme Immobilisation Influence and Viable Approaches
2.4. Non-Enzymatic Sensors
3. Implementation of Lactate Biosensors on Biomedicine: Real-Time Health Care
Biosensor | Electrode | Immobilisation Process | LRR (μM) | Sensi. (µA/mM) | LOD (µM) | Tr (s) | Lifetime (Days) | Samp. | App. | Ref. |
---|---|---|---|---|---|---|---|---|---|---|
Lactate Oxidase Biosensors | ||||||||||
MWCNT/TTF/LOx/Chit | Carbon ink | Crosslinking | 1000–20,000 | 0.644 | - | - | 152 | Sweat | Physical exercise intensity monitoring | [80] |
PB/LOx/Chit/AuNWs | AuNWs | - | 0–30,000 | 0.69 | 137 | 10 | 6 | Sweat | Physical exercise intensity monitoring | [104] |
LOx/BSA/PEGDE/β-cysteamine/AuNNs/Au | Au | Crosslinking | 1000–25,000 | 0.65 | 54 | - | 28 | Sweat | - | [105] |
LOx/PtNPs/GO/Au/SFNFs | Au | Entrapment | 400–6000 | - | - | - | - | Sweat | Physical exercise intensity monitoring | [82] |
ETH 500-PVC- DOS/LOx/PB/SPE | Carbon ink | - | 1000–25,000 | 0.0094 | 110 | 50 | - | Sweat | Physical exercise intensity monitoring | [75] |
LOx/PANHS/GO/Pd/Polyamide | Pd | Crosslinking | 1000–100,000 | - | 1000 | - | - | Sweat | - | [89] |
Nafion-LOx/PPy/MWCNT/PA6 | Pt | - | 0.001–1000 | - | - | 0.8 | - | Sweat | Physical exercise intensity monitoring | [90] |
PDDA/LOx/ZnO/MWCNT/PG | PG | Adsorption | 200–2000 | 7.3 | 6 | 6 | 120 | Serum | - | [106] |
LOx/sol-gel/MWCNTs/GCE | GCE | Sol–gel | 200–2000 | 6.031 | 0.3 | 5 | 28 | Serum | - | [107] |
PB-PPD-LOx-mouthguard | Prussian blue graphite ink | Electropolymeric entrapment | 100–1000 | 0.00055 | 50 | - | - | Saliva | Health and physical exercise monitoring | [84] |
Pt/o-PD/PEG/BSA/Chit-LOX-Pt-Ceria-AO | Pt | Adsorption | 0.0001–15,500 | - | 0.0001 | 6 | 21 | Rat tissues | Monitoring in vitro and in vivo tissues during hypoxia conditions | [108] |
LOx/cMWCNT/CuNPs/PANI/PGE | PGE | Covalent | 1–2500 | - | 0.25 | 5 | 140 | Plasma | Lactate acidosis diagnosis | [96] |
Nafion/LOx-GO-Ch/PB/SPE | Graphite | - | 1000–50,000 | 0.072 | 0.02 | - | - | Buffer solution | - | [109] |
Au/MoO3/LOx/Nafion | Au | - | 500–8000 | 0.87 | 150 | 10 | 16 | - | - | [110] |
HRP-PEGDGE-Os/Chit-LOx/polyphenol | Graphite paste | Crosslinking | 100–1000 | 0.763 | 13 | - | 91 | Saliva | - | [111] |
MWCNT/FcMe/Chit/HRP/BSA/LOx/SPBGE | SPCE | Entrapment | 30.4–243.9 | 3.42 | 22.6 | - | 150 | Embryonic cell culture | Growth evaluation of embryo | [19] |
Lactate Dehydrogenase Biosensors | ||||||||||
LDH/RGO-AuNPs/SPCE | SPCE | Entrapment | 10–5000 | 77 | 0.13 | 8 | 25 | Serum | Cancer biomarker detection | [112] |
LDHNPs/Au | Au | Covalent binding | 0.01–55,000 | 10.83 | 0.01 | 2.5 | 210 | Serum | Cardiogenic shock diagnosis | [94] |
LDH/GrONPs/PGE | PGE | Covalent binding | 5000–50,000 | - | 0.1 | 5 | 60 | Serum | Lactate acidosis diagnosis | [97] |
AuNP-cysteamine-LDH/Nafion/MWE | W | - | 500–7000 | 2.45 | 411 | - | 18 | Serum | Lactate acidosis diagnosis | [91] |
LDH-NAD+/Fe3O4NPs/MWCNTs/GCE | GCE | Covalent binding | 50–500 | 7.67 | 5 | - | 14 | Serum | - | [92] |
LDH/MWCNTs/Chit/Au | Au | Covalent binding | 0–120 | - | 15 | 8 | 10 | Blood | Lactate acidosis diagnosis | [98] |
LDH/MWCT-MB | CPE | Crosslinking | 100–10,000 | 0.42 | 7.5 | - | - | Blood | Physical exercise intensity monitoring | [113] |
LDH/MG/SWNT/GCE | GCE | Crosslinking | 200–10,000 | 0.0256 | 160 | - | 8 | Rat cardiomyocyte cell culture | Monitoring of cardiomyocytes during hypoxia | [114] |
LDH-NAD+/pTTABA/DPC | DPC | Covalent binding | 0.5–4000 | 0.02 | 0.112 | - | 60 | Extracellular matrix of cancer cells | Cancer diagnosis and antitumour activity evaluation | [95] |
LDH-GPT/SPCE | SPCE | - | 100–1000 | 0.033 | 5 | 300 | - | Cell cultures, sweat | Growth evaluation of cells, physical exercise intensity monitoring | [115] |
NADH/LDH/Nano-CeO2/GCE | GCE | Electrostatic interactions | 200–2000 | 571.19 | 50 | 4 | - | Buffer solution | - | [93] |
Other Enzyme and Non-enzyme Sensors | ||||||||||
FC b2/nAu-Au | Au | - | 300–2000 | 5.33 | - | - | 91 | Sweat, saliva | - | [116] |
MIPs-AgNWs | Carbon | - | 1–100,000 | 0.0045 | 0.22 | - | 212 | Sweat | Physical exercise intensity monitoring | [60] |
Cu2(NDC)2/PDHP | PDHP | - | 50–22,250 | 114 | 25 | 5 | - | Sweat | - | [117] |
NH2-GP-Cu3(btc)2 | GP | - | 0.05–22.6 | - | 5 | - | - | Sweat | - | [57] |
SPCE-NiCo (layered double hydroxide) | SPCE | - | 2–26 | 4.70 | 400 | - | 28 | Sweat | Physical exercise intensity monitoring | [58] |
Commercial Biosensors (Lactate Oxidase-Based) | ||||||||||
StatStrip® Lactate | - | - | 300–20,000 | - | - | 13 | 91 | Blood (0.6 µL) | Medical monitoring | [118] |
StatStrip Xpress® Lactate | - | - | 300–20,000 | - | - | 13 | 91 | Blood (0.6 µL) | Medical monitoring | [118] |
Lactate Plus Version 2 | - | - | 300–25,000 | - | - | 13 | - | Blood (0.6 µL) | Physical performance monitoring | [119] |
LactatEDGE | - | - | 700–22,000 | - | - | 45 | 91 | Blood (0.3 µL) | Physical performance monitoring | [120] |
Lactate Pro 2 (LT-1730) | - | - | 500–25,000 | - | - | 15 | - | Blood (0.3 µL) | Physical performance monitoring | [121] |
Lactate Scout 4 | - | - | 500–25,000 | - | - | 10 | Blood (0.2 µL) | Physical performance monitoring | [122] | |
Biosen C-Line (glucose and lactate) | - | - | 500–40,000 | - | - | 20–45 | 50 | Blood, plasma or serum (20 µL) | Medical monitoring | [123] |
4. Rise of Lactate Biosensors on the Food Industries: Proficient Quality Control
Biosensor | Electrode | Immobilisation Process | LRR (μM) | Sens. (µA/mM) | LOD (µM) | Tr (s) | Lifetime (Days) | Samp. | App. | Ref. |
---|---|---|---|---|---|---|---|---|---|---|
LOx/3,4DHS–AuNP/SPCE | SPCE | - | 2.6–800 | 5.1 | 2.6 | - | 30 | White wine, yoghurt, beer | Quality evaluation | [135] |
laponite/Chit/LOx/GCE | GCE | - | 10–700 | 11.41 | 3.8 | 4 | 30 | White wine, beer, fermented milk | - | [134] |
LOx-PVC-NH2-Quinhydrone- Graphite | Graphite | - | 50–10,000 | - | 20 | 10 | - | Buttermilk, pickle Juice | - | [136] |
LOx-Pt&Pd-Nafion-carbon | Carbon | - | 50–800 | - | 0.1 | 5 | 28 | Wine | Quality evaluation | [124] |
LOx–Cu-MOF/Chit/Pt/SPCE | SPCE | Crosslinking | 0.75–1000 | 14.65 | 0.75 | - | 50 | Red wine, white wine | Control of malolactic fermentation | [133] |
PtNPs/GCNF–PEI–GA–LOx–Gly–SPCE | SPCE | Covalent | 10–2000 | 0.025 | 6.9 | - | 547 | Wine, ciders | Analysis of lactic acid | [135] |
LODP/HRP-AuIDE | AuIDE | - | 0.05–210 | - | 0.05 | - | 35 | Yogurt | - | [133] |
GOx-LOx-BSA-GA-Au | Au | Covalent | 5–1000 | 0.75 | - | 10 | 85 | Red wine, white wine | Quality evaluation | [134] |
N-eicosane-MWCN-LOx-HRP-GPE | GPE | - | 5–244 | 3.47 | 0.96 | 65 | 456 | Beverages, wines, sauces | - | [136] |
DLDH/DP-TTF-Au | Au | Entrapment | 11–42 | 4.095 | 0.34 | - | 9 | Beer | Simultaneous determination of lactate enantiomers | [125] |
GA-LDH/AuNPs-ERGO-PAH/SPE | SPE | Crosslinking | 500–3000 | - | 1 | - | 49 | Yoghurt, wine | Quality evaluation | [41] |
5. Conclusions and Future Perspectives
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Enzymatic Sensors | ||||||
---|---|---|---|---|---|---|
Sensor Architecture | Trans. | LOD (µM) | Sensitivity | LRR (mM) | Sample Applied | Ref |
PtE-PDA/PPy/LOx | Amp. | - | 37.53 µA mM−1 cm−2 | 0–0.5 | PBS | [38] |
PtµE-poly-m-phenylene diamine/poly(ethylene glycol) diglycidyl ether)-LOx | Amp. | 19 ± 7 | 2.63 ± 0.66 nA mM−1 | 0–1.0 | Cerebrospinal fluid in mouse brain | [39] |
CE-fSWCNTs/Chit-PBNPs/Chit LOx | Amp. | 200 | - | 1–25 | Human sweat | [40] |
SPE-ERGO-PAH-AuNPs/LDH-GA | Amp. | 1 | 1.08 µA mM−1·cm−2 | 0–3 | Wine | [41] |
SPCE-PEGDGE/AvLOx | Amp. | 25 | 13 µA mM−1 cm−2 | 0–1 | PBS | [42] |
PtE-poly(phenylenedi- amine)/LOx/glycerol/PVA-SbQ | Amp. | 5 | 204 nA mM−1 | 0.005–1 | Blood serum | [43] |
Au-PB-Chit/CNTs-LOx-Chit/CNts | Amp. | - | 220 nA mM−1 | 0–30 | Sweat | [44] |
PVC/FC-LDH | Pot. | - | 52 mV decade −1 | - | Tris buffer | [45] |
AuE-LOx/GA/ZnO nanorod | Pot. | 0.1 | 41.33 ± 1.58 mV decade−1 | 0.0001–1 | PBS | [46] |
Si3N4-PAA/NHS-EDC/LOx | Pot. | 0.0002 | 49.7 mV decade−1 | 0–0.00005 | PBS | [47] |
Ti-Au/Nafion/Chit/LDH/GA | GFET | - | - | 0–7.5 | Human plasma | [48] |
Au-Os redox polymer/LOx | OFETs | - | - | 0–10 | PBS | [49] |
Non-enzymatic sensors | ||||||
GCE-Nafion/NiO | Amp. | 27 | 62.35 μA mM−1 cm−2 | 0.01–7.75 | NaOH | [50] |
GCE-Nafion/Co3O4 | Volt. | 6 | - | 0.5–3.0 | NaOH | [51] |
Amp. | 10 | |||||
GCE-CuO/MWCNTs/Nafion | Volt. | 0.088 | 633.0 pA mM−1 cm−2 | 0.0001–10 | Serum samples | [52] |
Ti-PTFE/PPy-MWCNTs | Amp. | 51 | 2.9 µAmM−1 cm−2 | 1–15 | Sweat | [53] |
BDD-NiNPs | Amp. | 0.72 ± 0.09 | (24.70 ± 0.36) μA L C−1 mol−1 | 6–120 | NaOH | [54] |
SPCE-NiCo layered double hydroxide | Amp. | 533 | 30.59 ± 0.34 μA mM−1 cm−2 | 5–25 | NaOH | [55] |
NiF-NiS-NC@NiS-MS | Amp. | 0.5 | 0.39 μA μM−1 | 0.0005–0.085 | Urine | [56] |
NH2-GP-Cu3(btc)2 | Amp. | 5 | 0.029 mA mM−1 cm−2 | 0.05–22.6 | Sweat | [57] |
SPCE-NiCo (layered double hydroxide) | Amp. | 400 | 83.98 μA mM−1 cm−2 | 2–26 | Sweat | [58] |
GCE-rGO-AuNPs-MIP | Amp. | 9 × 10−5 | 1.9 × 105 μA L mol−1 | 1 × 10−7–1 10−6 | Sugarcane vinasse | [59] |
CE-AgNWs-MIP | Amp. | 0.22 | 4.5 × 10−6 A M−1 | 0.001–100 | Sweat | [60] |
GCE-Nafion/CuO | Amp. | - | 80.33 μA mM−1 | 0.01–27.76 | - | [61] |
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García-Guzmán, J.J.; Sierra-Padilla, A.; Palacios-Santander, J.M.; Fernández-Alba, J.J.; Macías, C.G.; Cubillana-Aguilera, L. What Is Left for Real-Life Lactate Monitoring? Current Advances in Electrochemical Lactate (Bio)Sensors for Agrifood and Biomedical Applications. Biosensors 2022, 12, 919. https://doi.org/10.3390/bios12110919
García-Guzmán JJ, Sierra-Padilla A, Palacios-Santander JM, Fernández-Alba JJ, Macías CG, Cubillana-Aguilera L. What Is Left for Real-Life Lactate Monitoring? Current Advances in Electrochemical Lactate (Bio)Sensors for Agrifood and Biomedical Applications. Biosensors. 2022; 12(11):919. https://doi.org/10.3390/bios12110919
Chicago/Turabian StyleGarcía-Guzmán, Juan José, Alfonso Sierra-Padilla, José María Palacios-Santander, Juan Jesús Fernández-Alba, Carmen González Macías, and Laura Cubillana-Aguilera. 2022. "What Is Left for Real-Life Lactate Monitoring? Current Advances in Electrochemical Lactate (Bio)Sensors for Agrifood and Biomedical Applications" Biosensors 12, no. 11: 919. https://doi.org/10.3390/bios12110919
APA StyleGarcía-Guzmán, J. J., Sierra-Padilla, A., Palacios-Santander, J. M., Fernández-Alba, J. J., Macías, C. G., & Cubillana-Aguilera, L. (2022). What Is Left for Real-Life Lactate Monitoring? Current Advances in Electrochemical Lactate (Bio)Sensors for Agrifood and Biomedical Applications. Biosensors, 12(11), 919. https://doi.org/10.3390/bios12110919