Evidence map›Paper›PMID 41816357›Full record

ReviewFrontiers in cellular and infection microbiology2026

CRISPR-based diagnostics for infectious diseases: mechanisms, advancements and clinical transformation prospects.

Zhenzhen Pan, Ling Xu, Zihao Fan, Yaling Cao, Feng Ren

Abstract readReview
In one paragraph

Review in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zhenzhen PanBeijing Institute of Hepatology, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Ling XuBeijing Institute of Hepatology, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Zihao FanBeijing Institute of Hepatology, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Yaling CaoBeijing Institute of Hepatology, Beijing Youan Hospital, Capital Medical University, Beijing, China.
Feng RenBeijing Institute of Hepatology, Beijing Youan Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Infectious diseases continue to pose significant global public health challenges, necessitating the development of rapid, sensitive, specific, and field-deployable diagnostic platforms. The discovery of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated proteins (Cas) has revolutionized genome editing and concurrently enabled a new generation of molecular diagnostic tools. Leveraging the inherent trans-cleavage activities of Cas enzymes, platforms such as SHERLOCK (Specific High-sensitivity Enzymatic Reporter unLOCKing) and DETECTR (DNA Endonuclease-Targeted CRISPR Trans Reporter) have emerged, combining target recognition precision with reporter systems to achieve ultra-sensitive detection of pathogen-specific nucleic acids. This review systematically examines the mechanistic foundations of CRISPR diagnostics, synthesizes recent advancements in infectious disease applications, evaluates their advantages in sensitivity, specificity, operational simplicity, and multiplexing capacity, and critically analyzes current implementation barriers and future translational pathways.

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsCommunicable DiseasesCRISPR-Cas SystemsMolecular Diagnostic TechniquesGene EditingHumansSensitivity and SpecificityCas proteinsCRISPRinfectious diseasesmolecular diagnosticspoint-of-care

Identifiers

PMID41816357
PMCPMC12971636

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.