Evidence map›Paper›PMID 42168636›Full record

ArticleAnalytical and bioanalytical chemistry2026

Reusable 3D-printed microfluidic-on-fabric with modular electrodes for point-of-care Na

Tao Zhang, Grayson Ruffner, Sarah Varney, Inchan Baek, Bella Fong, Hui Chen, Chengpeng Chen

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In one paragraph

Article in Analytical and bioanalytical chemistry, 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
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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.

Tao ZhangDepartment of Chemistry and Biochemistry, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD, 21250, USA.
Grayson RuffnerDepartment of Chemistry and Biochemistry, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD, 21250, USA.
Sarah VarneyDepartment of Chemistry and Biochemistry, James Madison University, 901 Carrier Drive, Harrisonburg, VA, 22801, USA.
Inchan BaekPhillips Academy, Andover, MA, 01810, USA.
Bella FongDepartment of Chemistry and Biochemistry, James Madison University, 901 Carrier Drive, Harrisonburg, VA, 22801, USA.
Hui ChenDepartment of Chemistry and Biochemistry, James Madison University, 901 Carrier Drive, Harrisonburg, VA, 22801, USA. chen22hx@jmu.edu.
Chengpeng ChenDepartment of Chemistry and Biochemistry, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD, 21250, USA. cpchen@umbc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we present a new 3D-printed microfluidic-on-fabric sensor platform that allows for point-of-care (POC) detection in various biofluids. Using the low-cost FDM 3D-printing, we developed a method to form well-defined microfluidic features on fabric substrates (3D-printed microfluidic-on-fabric), which could modularly house an electrode pad with desired electrodes targeting different analytes. The 3D-printed microfluidic-on-fabric integrates the comfort, robustness, and reusability (after washing) of fabric substrates with the precision, modularity, and scalability offered by 3D-printed structures. We showcased the application of the sensor platform for Na⁺ and K⁺ detections with lab-made ion-selective electrode pads. The electrodes showed high reusability, in addition to the robust Nernst sensitivity, accuracy, selectivity, and reproducibility (linear range = 5-500 mM; LOD(Na⁺) = 1.5 mM and LOD(K

Indexed as

Body FluidsMicrofluidic Analytical TechniquesPoint-of-Care SystemsPotassiumPrinting, Three-DimensionalSodiumElectrodesEquipment DesignHumansIon-Selective ElectrodesLimit of DetectionReproducibility of ResultsPotassiumSodium3D-printingMicrofluidicsPoint-of-careSensor

Identifiers

PMID42168636
PMCPMC13375825

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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.