Evidence map›Paper›PMID 42077856›Full record

ArticleACS omega2026

Split-crRNA Transcription Based Dual-Recognition Cascade Amplification Assay for Sensitive and Accurate Postoperative Delirium Related MicroRNA Analysis.

Lihua Wang, Huihui Li, Kai Wang, Jinge Ma, Guosheng Liu, Ning Li, Baojun Zhang

Abstract read
In one paragraph

Article in ACS omega, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Lihua WangDepartment of Anesthesiology and Perioperative Medicine, Xinxiang Central Hospital (The Fourth Clinical College of Henan Medical University), Xinxiang City, Henan Province, 453000, China.
Huihui LiDepartment of Anesthesiology and Perioperative Medicine, Xinxiang Central Hospital (The Fourth Clinical College of Henan Medical University), Xinxiang City, Henan Province, 453000, China.
Kai WangDepartment of Anesthesiology and Perioperative Medicine, Xinxiang Central Hospital (The Fourth Clinical College of Henan Medical University), Xinxiang City, Henan Province, 453000, China.
Jinge MaDepartment of Anesthesiology and Perioperative Medicine, Xinxiang Central Hospital (The Fourth Clinical College of Henan Medical University), Xinxiang City, Henan Province, 453000, China.
Guosheng LiuDepartment of Anesthesiology and Perioperative Medicine, Xinxiang Central Hospital (The Fourth Clinical College of Henan Medical University), Xinxiang City, Henan Province, 453000, China.
Ning LiDepartment of Anesthesiology and Perioperative Medicine, Xinxiang Central Hospital (The Fourth Clinical College of Henan Medical University), Xinxiang City, Henan Province, 453000, China.
Baojun ZhangDepartment of Anesthesiology and Perioperative Medicine, Xinxiang Central Hospital (The Fourth Clinical College of Henan Medical University), Xinxiang City, Henan Province, 453000, China.ORCID https://orcid.org/0009-0005-5582-6779

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Postoperative delirium (POD) represents a serious neuropsychiatric complication, underscoring the urgent need for sensitive and specific detection of circulating microRNAs (miRNAs) as potential biomarkers. Conventional isothermal amplification methods, however, often face a trade-off between sensitivity and specificity. Herein, we report a cascade amplification strategy that integrates catalytic hairpin assembly (CHA), split DNAzyme cleavage, T7 RNA polymerase-mediated transcription, and CRISPR-Cas12a

Identifiers

PMID42077856
PMCPMC13129835

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.