The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
SHERLOCK and DETECTR: CRISPR-Cas Systems as Potential Rapid Diagnostic Tools for Emerging Infectious Diseases
Open accessAbstract
Infectious diseases are one of the most intimidating threats to human race, responsible for an immense burden of disabilities and deaths. Rapid diagnosis and treatment of infectious diseases offers a better understanding of their pathogenesis. According to the World Health Organization, the ideal approach for detecting foreign pathogens should be rapid, specific, sensitive, instrument-free, and cost-effective. Nucleic acid pathogen detection methods, typically PCR, have numerous limitations, such as highly sophisticated equipment requirements, reagents, and trained personnel relying on well-established laboratories, besides being time-consuming.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Global trends in emerging infectious diseases
Jones, K. E., Patel, N. G., Levy, M. A., Storeygard, A., Balk, D., Gittleman, J. L., & Daszak, P. (2008) · Nature · doi:10.1038/nature06536 · Cited by 8,338
The new frontier of genome engineering with CRISPR-Cas9
Doudna, J. A., & Charpentier, E. (2014) · Science · doi:10.1126/science.1258096 · Cited by 7,062
CRISPR-Cas12a target binding unleashes indiscriminate single-stranded DNase activity
Chen, J. S., Ma, E., Harrington, L. B., Da Costa, M., Tian, X., Palefsky, J. M., & Doudna, J. A. (2018) · Science · doi:10.1126/science.aar6245 · Cited by 4,507
SARS and MERS: recent insights into emerging coronaviruses
de Wit, E., van Doremalen, N., Falzarano, D., & Munster, V. J. (2016) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2016.81 · Cited by 3,510
RNA-guided editing of bacterial genomes using CRISPR-Cas systems
Jiang, W., Bikard, D., Cox, D., Zhang, F., & Marraffini, L. A. (2013) · Nature Biotechnology · doi:10.1038/nbt.2508 · Cited by 2,429
RNA targeting with CRISPR–Cas13
Abudayyeh, O. O., Gootenberg, J. S., Essletzbichler, P., Han, S., Joung, J., Belanto, J. J., Verdine, V., Cox, D. B. T., Kellner, M. J., Regev, A., et al. (2017) · Nature · doi:10.1038/nature24049 · Cited by 2,093
CRISPR-Cas guides the future of genetic engineering
Knott, G. J., & Doudna, J. A. (2018) · Science · doi:10.1126/science.aat5011 · Cited by 1,410
Non-viral delivery systems for CRISPR/Cas9-based genome editing: challenges and opportunities
Li, L., Hu, S., & Chen, X. (2018) · Biomaterials · doi:10.1016/j.biomaterials.2018.04.031 · Cited by 415
Cited by
Ultrasensitive and Highly Specific Lateral Flow Assays for Point-of-Care Diagnosis
Liu, Y., Zhan, L., Qin, Z., Sackrison, J., & Bischof, J. C. (2021) · ACS Nano · doi:10.1021/acsnano.0c10035 · Cited by 626
Huang, Y., Guo, X., Wu, Y., Chen, X., Feng, L., Xie, N., & Shen, G. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01745-z · Cited by 490
CRISPR-Driven Biosensors: A New Frontier in Rapid and Accurate Disease Detection
Razavi, Z., Soltani, M., Souri, M., & Pazoki-Toroudi, H. (2026) · Critical Reviews in Analytical Chemistry · doi:10.1080/10408347.2024.2400267 · Cited by 45
Metadata
- Authors
- Mustafa, M. I., & Makhawi, A. M.
- Venue
- Journal of Clinical Microbiology
- Publisher
- American Society for Microbiology
- Published
- 2021-02-18
- Volume
- 59
- Issue
- 3
- ISSN
- 0095-1137 (ISSN-L)
- 1098-660X
- OpenAlex
- W3097972923
- Cited by
- 232
- References
- 8
- FWCI
- 9.14
- Type
- journal article
- Language
- en
- Status
- Retracted
- Open access
- hybrid
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: SHERLOCK and DETECTR: CRISPR-Cas Systems as Potential Rapid Diagnostic Tools for Emerging Infectious Diseases. https://app.cochat.ai/papers/10.1128/jcm.00745-20
- The paper
- Mustafa, M. I., & Makhawi, A. M. (2021). SHERLOCK and DETECTR: CRISPR-Cas Systems as Potential Rapid Diagnostic Tools for Emerging Infectious Diseases. Journal of Clinical Microbiology. https://doi.org/10.1128/jcm.00745-20
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.