Evidence map›Paper›PMID 42425947›Full record

ArticleMicrosystems & nanoengineering2026

A microfluidic hollow-fiber infection model (µHFIM): monitoring bacterial response to dynamic drug treatment with single-cell resolution.

Friederike-Leonie Born, Raphael Dezauzier, Annelies S Zinkernagel, Petra S Dittrich

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 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

4 authors.

Friederike-Leonie BornDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Raphael DezauzierDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Annelies S ZinkernagelDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Petra S DittrichDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland. petra.dittrich@bsse.ethz.ch.ORCID http://orcid.org/0000-0001-5359-8403

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) 51NF40_180541
6 · The paper itself

Abstract

Antibiotic resistance is a growing global health threat. To improve our understanding of the mechanisms driving antibiotic resistance, suitable infection models are needed that also capture relevant drug dynamics. Here, we present a microfluidic hollow-fiber infection model that enables pharmacokinetic/pharmacodynamic studies under physiologically relevant conditions. The system simulates temporally antibiotic concentration gradients (pharmacokinetic module) and enables the long-term, high-resolution imaging of bacterial cells within a tissue-like hydrogel matrix in a flat growth chamber (pharmacodynamic module) with minimum sample and drug consumption. Using Escherichia coli quality control strains exposed to amoxicillin and amoxicillin-clavulanic acid, we show that treatment efficacy is not determined solely by the fraction of time above the minimum inhibitory concentration. Instead, dosing intervals and recovery phases between doses critically shape bacterial survival and killing. Prolonged dosing phases (>6 h) or shortened recovery periods enhance bacterial clearance, while specific dynamic regimens induce distinct phenotypic responses, including filamentous growth. In addition, the system supports analysis of clinical isolates via inline staining. By combining dynamic PK control, tissue-like hydrogel environments, and sustained high-resolution imaging, the µHFIM enables in vivo-like investigation of bacterial responses to antibiotic treatment. This system provides mechanistic insight into how dosing schedules govern efficacy and adaptation, which may help to optimize antibiotic treatment strategies in the future (bench to bedside translation).

Identifiers

PMID42425947
PMCPMC13351019

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.