Evidence map›Paper›PMID 42536747›Full record

ArticleScience advances2026

A lab-on-a-silicon-chip platform for all-electrical antibiotic susceptibility tests with a sample-to-results time within 20 minutes.

Zheqiang Xu, Victoria C Nolan, Yingtao Yu, Petra Muir, Sanna Koskiniemi, Zhen Zhang

Abstract read
In one paragraph

Article in Science advances, 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

6 authors.

Zheqiang XuÅngström Laboratory, Division of Solid-State Electronics, Department of Electrical Engineering, Uppsala University, SE-75121 Uppsala, Sweden.ORCID 0000-0002-5477-9019
Victoria C NolanÅngström Laboratory, Division of Solid-State Electronics, Department of Electrical Engineering, Uppsala University, SE-75121 Uppsala, Sweden.ORCID 0009-0000-9517-8976
Yingtao YuÅngström Laboratory, Division of Solid-State Electronics, Department of Electrical Engineering, Uppsala University, SE-75121 Uppsala, Sweden.ORCID 0000-0001-5495-0253
Petra MuirDepartment of Cellular and Molecular Biology, Uppsala University, SE-75124 Uppsala, Sweden.ORCID 0000-0002-9499-9227
Sanna KoskiniemiDepartment of Cellular and Molecular Biology, Uppsala University, SE-75124 Uppsala, Sweden.ORCID 0000-0002-3275-0936
Zhen ZhangÅngström Laboratory, Division of Solid-State Electronics, Department of Electrical Engineering, Uppsala University, SE-75121 Uppsala, Sweden.ORCID 0000-0003-4317-9701

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid antibiotic susceptibility tests (ASTs) are essential for quick selection of effective drugs to treat infections at an early stage. However, the most widely used phenotypic ASTs in clinical practice often require 24 to 48 hours of pre-culture enrichment and 4 to 20 hours of testing. They are too slow to guide therapy, even with the most rapid protocol. Here, we report a lab-on-a-silicon chip (LOSC) system, which integrates arrays of silicon nanowire field-effect transistor (SiNWFET) sensors with high-throughput cell-collection microfluidics for rapid ASTs. The microfluidics concentrate bacteria into picoliter-scale chambers within minutes, eliminating the need for pre-cultivation. Embedded SiNWFETs sensitively track antibiotic-induced metabolic pH shifts, enabling AST by detecting rapid metabolic inhibition in susceptible bacteria. Using an unbuffered culturing medium, LOSC achieves sample-to-result times within 20 minutes for clinically isolated uropathogenic

Indexed as

Anti-Bacterial AgentsLab-On-A-Chip DevicesSiliconEscherichia coliHumansMicrobial Sensitivity TestsMicrofluidicsNanowiresTime FactorsAnti-Bacterial AgentsSilicon

Identifiers

PMID42536747
PMCPMC13426434

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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.