MOF-Based Platform for Kidney Diseases: Advances, Challenges, and Prospects
Abstract
:1. Introduction
2. Application of MOFs in the Kidney Diseases Diagnosis
2.1. Biomarkers in Urine
2.2. Biomarkers of Respiratory Gases
2.3. Biomarkers in Other Samples
3. Application of MOFs in Kidney Disease Treatment
3.1. MOFs as a Uremic Toxin Adsorbent for the Kidney Disease Treatment
3.1.1. Zr-Based MOFs
3.1.2. Fe-Based MOFs
3.1.3. Other Types of MOFs
3.2. MOFs as a Drug Carrier for the Treatment of Kidney Disease
3.3. Other Treatment Methods
4. Conclusions, Challenges, and Prospects
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Biological Sample | MOF-Based Agents | Biomarkers Detected | Advantages | Limitations | Ref. |
---|---|---|---|---|---|
Urine | Au@MIL-101(Fe) | Creatinine | Non-invasive. Low detection limit. Wide linear response range. | Lack of long-term stability studies. Lack of reusability studies. Lack of adequate clinical validation. | [35] |
Mag Zr-MOF@G6P | Glyco- proteins | Non-invasive. Low detection limit. Good selectivity. | Complex recovery process. Limited enrichment capacity. | [43] | |
Fe3O4@NH2-MIL- Ti@TTA-MA | Glyco- and phospho- proteins | Non-invasive. Low detection limit. Good selectivity. Good reusability. Synergistic. | Inadequate sample representation. Lack of long-term stability studies. Lacks adequate clinical validation. | [44] | |
Ti-MOF-MO | Specific metabolites (Arg, His, Glu) | Non-invasive. Low detection limit. Low sample consumption. High diagnostic accuracy. | Not portable. High cost of synthesis. Lack of metabolite database support. Lack of adequate clinical validation. | [49] | |
Breathe gas | ZENose (Fc@ZIF-8) | Ammonia | Non-invasive. Low detection limit. Wide linear response range. Remote Point of Care (POC). | Electrode regeneration is unknown. Lack of long-term stability studies. Lack of adequate clinical validation. | [62] |
Blood | UiO-HQCA-Al | Creatinine | Low detection limit. Wide linear response range. Fast response. High selectivity. | Environmentally sensitive. Lack of adequate clinical validation. | [67] |
Tears | Cu-BDC MOF/GO- Cu(II)/Cu2O NPs | Creatinine | Non-invasive. High selectivity and sensitivity. Precise predictive capability. Remote Point of Care (POC). | High cost of synthesis. Lack of adequate clinical validation. Deficiencies in the generalization ability of machine learning models. | [71] |
MOFs Classification | MOFs and Their Composites | Uremic Toxins | Adsorption Capacity (mg·g−1 MOF) | Removal Efficiency (%) | Ref. |
---|---|---|---|---|---|
Zr-based MOFs | NU-1000 | pCS | 294.9 | 94 | [81] |
IS | Not available | 98 | [81] | ||
UiO-66 | HA | Not available | 2.1 | [81] | |
PPNUH | pCS | 282.0 | 85 | [88] | |
IS | 329.0 | 85 | [88] | ||
UiO-66-NH3 (75%) | IS | Not available | 80 | [90] | |
HA | Not available | 83 | [90] | ||
UiO-66-NH2 (75%) 12.5% HCl | IS | Not available | 80 | [90] | |
HA | Not available | 77 | [90] | ||
UiO-66-(COOH)2@ cotton fabric | Creatinine | 212.8 | 98 | [95] | |
UiO-66-(COOH)2@PAN (UAPNFM) | Creatinine | 168.6 | 82 | [97] | |
UiO-66-(COOH)2@ PVA/PAN TFNC | Creatinine | 54.0 | Not available | [98] | |
Fe-based MOFs | MIL-53(Fe) | Urea | 635.0 | 96 | [103] |
MIL-100(Fe) | Urea | 692.0 | 97 | [103] | |
pCS | 12.9 | 65 | [106] | ||
Creatinine | 190.5 | 89 | [108] | ||
Bio-MOFs | Bio-MOF-11 (YUVSUE) | Urea | 38.7 | Not available | [107] |
Bio-MOF-12 (BEYSEF) | Urea | 63.6 | Not available | [107] | |
Methionine-derived MOF (OREZES) | IS | 2100.0 | 98 | [115] | |
Urea | 347.9 | Not available | [115] | ||
Cationic MOFs | ZJU-X6 | pCS | 197.2 | 98 | [125] |
IS | 230.4 | 94 | [125] | ||
ZJU-X7 | pCS | 57.0 | 78 | [125] | |
IS | 118.6 | 97 | [125] | ||
Isoreticular MOFs (IRMOFs) | A(0.2)-IRMOF-1@SiO2 | Urea | 1325.7 | 92 | [129] |
Creatinine | 625.0 | 80 | [129] | ||
Cu-based MOFs | Cu3(BTC)2 | Urea | 250.0 | Not available | [130] |
Cu-BTC@PDA/PAN nanofiber | Urea | 152.4 | 92 | [131] | |
Creatinine | 100.50 | 82 | [131] |
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Deng, L.-E.; Guo, M.; Deng, Y.; Pan, Y.; Wang, X.; Maduraiveeran, G.; Liu, J.; Lu, C. MOF-Based Platform for Kidney Diseases: Advances, Challenges, and Prospects. Pharmaceutics 2024, 16, 793. https://doi.org/10.3390/pharmaceutics16060793
Deng L-E, Guo M, Deng Y, Pan Y, Wang X, Maduraiveeran G, Liu J, Lu C. MOF-Based Platform for Kidney Diseases: Advances, Challenges, and Prospects. Pharmaceutics. 2024; 16(6):793. https://doi.org/10.3390/pharmaceutics16060793
Chicago/Turabian StyleDeng, Li-Er, Manli Guo, Yijun Deng, Ying Pan, Xiaoxiong Wang, Govindhan Maduraiveeran, Jianqiang Liu, and Chengyu Lu. 2024. "MOF-Based Platform for Kidney Diseases: Advances, Challenges, and Prospects" Pharmaceutics 16, no. 6: 793. https://doi.org/10.3390/pharmaceutics16060793
APA StyleDeng, L. -E., Guo, M., Deng, Y., Pan, Y., Wang, X., Maduraiveeran, G., Liu, J., & Lu, C. (2024). MOF-Based Platform for Kidney Diseases: Advances, Challenges, and Prospects. Pharmaceutics, 16(6), 793. https://doi.org/10.3390/pharmaceutics16060793