Transport-Reaction-Signal Coupling in Lateral Flow Assays for Next-Generation Point-of-Care Diagnostics.

Yan Pan, Yuewei Li, Chao Mi, Zhengwen Yang, Lana McClements, Steven J Langford, Jiayan Liao

Abstract readReview

In one paragraph

Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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.

Yan PanInstitute For Biomedical Materials and Devices (IBMD), Faculty of Science, University of Technology Sydney, Ultimo, New South Wales, Australia.ORCID https://orcid.org/0009-0001-6954-3498

Yuewei LiInstitute For Biomedical Materials and Devices (IBMD), Faculty of Science, University of Technology Sydney, Ultimo, New South Wales, Australia.

Chao MiSchool of Advanced Engineering, Great Bay Institute for Advanced Study, Great Bay University, Dongguan, Guangdong, China.

Zhengwen YangCollege of Materials Science and Engineering, Kunming University of Science and Technology, Kunming, China.ORCID https://orcid.org/0000-0001-6470-9244

Lana McClementsSchool of Life Sciences, Faculty of Science, University of Technology Sydney, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0002-4911-1014

Steven J LangfordSchool of Mathematical and Physical Sciences, Faculty of Science, University of Technology Sydney, Ultimo, New South Wales, Australia.ORCID https://orcid.org/0000-0001-7149-996X

Jiayan LiaoInstitute For Biomedical Materials and Devices (IBMD), Faculty of Science, University of Technology Sydney, Ultimo, New South Wales, Australia.ORCID https://orcid.org/0000-0003-0616-4762

Funding

Future Leader Fellowship 106628National Health and Medical Research Council 2025442National Natural Science Foundation of China 62575049UTS Chancellor's Research Fellowship Program PRO22-15457

6 · The paper itself

Abstract

Lateral flow assays (LFAs) remain central to point-of-care diagnostics because they combine low cost, portability, and operational simplicity. Emerging diagnostic demands, including low-abundance biomarkers, complex sample matrices, quantitative readout, and multiplexed analysis, increasingly expose limitations that cannot be solved by signal-label enhancement alone. This Review examines recent LFA advances through a three-phase framework that couples porous-material mass transfer, interfacial reaction engineering, and signal transduction. The framework clarifies how membrane and flow design regulate analyte delivery and residence time, how antibody orientation, reaction amplification, and hook-effect mitigation improve capture efficiency and dynamic range, and how advanced nanolabels, integrated readers, multiplexed formats, and AI/ML-supported design and analysis expand performance across the assay workflow. By distinguishing intrinsic performance gains from strategies that transfer complexity to reagents, devices, or software, this Review provides design principles for sensitive, quantitative, and translation-oriented LFA systems.

Indexed as

artificial intelligencefluid dynamicsimmunoreactionlateral flow assaynanomaterialspoint‐of‐care diagnosticsporous materialssignal transduction

Identifiers

PMID42813527

DOI10.1002/advs.77916

PMCPMC13625143

What Socratic 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 Socratic graph.