Evidence map›Paper›PMID 42662407›Full record

ReviewFood chemistry: X2026

Emerging multimodal lateral flow immunoassays: Rational signal synergy design for enhanced food safety monitoring.

Xuwen Wang, Beimeng Liang, Xinxin Kang, Long Han, Mengyue Guo, Jiaoyang Luo, Meihua Yang

Abstract readReview
In one paragraph

Review in Food chemistry: X, 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.

Xuwen WangKey Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.
Beimeng LiangKey Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.
Xinxin KangKey Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.
Long HanKey Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.
Mengyue GuoKey Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.
Jiaoyang LuoKey Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.
Meihua YangKey Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lateral flow immunoassay (LFIA) has become a core tool for rapid on-site screening of food hazards. However, traditional single-modal LFIA exhibits insufficient sensitivity and is susceptible to matrix interference, posing significant challenges in practical applications. In recent years, the systematic integration of multimodal signals, including colorimetric, catalytic, magnetic, fluorescence, and photothermal, has emerged as a critical strategy to improve detection sensitivity, anti-interference capability, and quantitative accuracy. Notably, the performance of multimodal LFIA depends on the design of functional materials and device support. Based on this, this review systematically summarizes four key aspects: 1) The intrinsic properties of diverse functional nanomaterials. 2) Device support from high-precision laboratory instruments to portable sensors, enhanced by artificial intelligence. 3) Practical applications for food contaminants monitoring in complex matrices. 4) Current bottlenecks and future prospects. This review aims to provide a valuable theoretical foundation for advancing multimodal LFIA toward more universal and user-friendly detection tool.

Indexed as

AI-enhanced detectionFood contaminantsImmunoassayNanoprobe designRapid screeningSignal synergy

Identifiers

PMID42662407
PMCPMC13519605

What OpenQuestion holds

Textmetadata
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.