Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 159

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

How CRISPR-Cas System Could Be Used to Combat Antimicrobial Resistance

Open access
Gholizadeh, Pourya, Köse, Şükran, Dao, Sounkalo, Ganbarov, Khudaverdi, Tanomand, Asghar, Dal, Tuba, Aghazadeh, Mohammad, Ghotaslou, Reza, Ahangarzadeh Rezaee, Mohammad, Yousefi, Bahman, Samadi Kafil, Hossein·2020·Infection and Drug Resistance

Abstract

Rapid emergence of antibiotic-resistant bacteria has made it harder for us to combat infectious diseases and to develop new antibiotics. The clustered regularly interspaced short palindromic repeats - CRISPR-associated (CRISPR-Cas) system, as a bacterial adaptive immune system, is recognized as one of the new strategies for controlling antibiotic-resistant strains. The programmable Cas nuclease of this system used against bacterial genomic sequences could be lethal or could help reduce resistance of bacteria to antibiotics. Therefore, this study aims to review using the CRISPR-Cas system to promote sensitizing bacteria to antibiotics. We envision that CRISPR-Cas approaches may open novel ways for the development of smart antibiotics, which could eliminate multidrug-resistant (MDR) pathogens and differentiate between beneficial and pathogenic microorganisms. These systems can be exploited to quantitatively and selectively eliminate individual bacterial strains based on a sequence-specific manner, creating opportunities in the treatment of MDR infections, the study of microbial consortia, and the control of industrial fermentation.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2147/idr.s247271

Cites

6 of 6 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 6 references

Cited by

See all 159

Metadata

Authors
Gholizadeh, P., Köse, Ş., Dao, S., Ganbarov, K., Tanomand, A., Dal, T., Aghazadeh, M., Ghotaslou, R., Ahangarzadeh Rezaee, M., Yousefi, B., & Samadi Kafil, H.
Venue
Infection and Drug Resistance
Published
2020-04
Volume
Volume 13
Pages
1111-1121
ISSN
1178-6973 (ISSN-L)
OpenAlex
W3016589929
Cited by
159
References
6
FWCI
5.95
Type
journal article
Language
en
Open access
gold

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: How CRISPR-Cas System Could Be Used to Combat Antimicrobial Resistance. https://app.cochat.ai/papers/10.2147/idr.s247271
The paper
Gholizadeh, P., Köse, Ş., Dao, S., Ganbarov, K., Tanomand, A., Dal, T., Aghazadeh, M., Ghotaslou, R., Ahangarzadeh Rezaee, M., Yousefi, B., & Samadi Kafil, H. (2020). How CRISPR-Cas System Could Be Used to Combat Antimicrobial Resistance. Infection and Drug Resistance. https://doi.org/10.2147/idr.s247271

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.