Evidence map›Paper›PMID 42542593›Full record

ArticleiScience2026

Development of colloidal gold and carbon immunochromatographic strips for rapid detection of PDCoV.

Chenlin Hao, Mengxiao Xu, Tong Bu, Bingqian Zhang, Zhiyang Ran, Xueshi Niu, Zhihui Chen, Xiaohui Jin, Yue Zhang, Zhanyong Wei and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 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

11 authors.

Chenlin HaoCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan 450002, China.
Mengxiao XuCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan 450002, China.
Tong BuHenan Engineering Technology Research Center of Food Processing and Circulation Safety Control, College of Food Science and Technology, Henan Agricultural University, Zhengzhou, Henan 450002, China.
Bingqian ZhangCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan 450002, China.
Zhiyang RanCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan 450002, China.
Xueshi NiuCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan 450002, China.
Zhihui ChenCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan 450002, China.
Xiaohui JinCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan 450002, China.
Yue ZhangCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan 450002, China.
Zhanyong WeiCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan 450002, China.
Honglei ZhangCollege of Veterinary Medicine, Henan Agricultural University, Zhengzhou, Henan 450002, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Porcine deltacoronavirus (PDCoV) is an enteric coronavirus that causes diarrhea in suckling piglets, leading to serious economic losses in the swine industry. In this study, we report the development of competitive immunochromatographic strips for PDCoV detection using both colloidal gold and carbon nanoparticles, which also represents the novel reported application of carbon nanoparticles in a viral immunochromatographic assay. The established strips had visual detection limits of 1:128 (gold) and 1:64 (carbon) at 1 × 10

Indexed as

gold and carbon nanoparticlesimmunochromatographic assayporcine deltacoronavirus

Identifiers

PMID42542593
PMCPMC13427578

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.