Evidence map›Paper›PMID 40230092›Full record

ArticleeLife2025

UFMTrack, an Under-Flow Migration Tracker enabling analysis of the entire multi-step immune cell extravasation cascade across the blood-brain barrier in microfluidic devices.

Mykhailo Vladymyrov, Luca Marchetti, Sidar Aydin, Sasha G N Soldati, Adrien Mossu, Arindam Pal, Laurent Gueissaz, Akitaka Ariga, Britta Engelhardt

Abstract read
In one paragraph

Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

9 authors.

Mykhailo VladymyrovTheodor Kocher Institute, Bern, Switzerland.ORCID https://orcid.org/0000-0002-5720-9740
Luca MarchettiTheodor Kocher Institute, Bern, Switzerland.
Sidar AydinTheodor Kocher Institute, Bern, Switzerland.ORCID https://orcid.org/0000-0001-7791-7931
Sasha G N SoldatiTheodor Kocher Institute, Bern, Switzerland.
Adrien MossuTheodor Kocher Institute, Bern, Switzerland.
Arindam PalTheodor Kocher Institute, Bern, Switzerland.ORCID https://orcid.org/0000-0002-3784-7868
Laurent GueissazTheodor Kocher Institute, Bern, Switzerland.ORCID https://orcid.org/0009-0008-8695-7992
Akitaka ArigaLaboratory for High Energy Physics, University of Bern, Bern, Switzerland.
Britta EngelhardtTheodor Kocher Institute, Bern, Switzerland.ORCID https://orcid.org/0000-0003-3059-9846

Funding

University of Bern UniBe ID Grant
6 · The paper itself

Abstract

The endothelial blood-brain barrier (BBB) strictly controls immune cell trafficking into the central nervous system (CNS). In neuroinflammatory diseases such as multiple sclerosis, this tight control is, however, disturbed, leading to immune cell infiltration into the CNS. The development of in vitro models of the BBB combined with microfluidic devices has advanced our understanding of the cellular and molecular mechanisms mediating the multistep T-cell extravasation across the BBB. A major bottleneck of these in vitro studies is the absence of a robust and automated pipeline suitable for analyzing and quantifying the sequential interaction steps of different immune cell subsets with the BBB under physiological flow in vitro. Here, we present the under-flow migration tracker (

Indexed as

Blood-Brain BarrierCell MovementLab-On-A-Chip DevicesAnimalsEndothelial CellsHumansTransendothelial and Transepithelial Migrationautomated analysisblood-brain barriercell biologycell tracking under flowhumanimmunologyinflammationleukocyte traffickingmachine learningmicrofluidicsmouse

Identifiers

PMID40230092
PMCPMC11999694

What OpenQuestion holds

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Registered trials

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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.