Evidence map›Paper›PMID 41969376›Full record

ArticleRSC advances2026

CellTrap: an instrument-free microfluidic platform for cell-cell interactions at stochastically generated effector-to-target ratios.

Muhammad Zia Ullah Khan, Morteza Hasanzadeh Kafshgari, Ali Bashiri Dezfouli, Oliver Hayden, Gabriele Multhoff, Ghulam Destgeer

Abstract read
In one paragraph

Article in RSC 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.

Muhammad Zia Ullah KhanControl and Manipulation of Microscale Living Objects, Center for Translational Cancer Research (TranslaTUM), Munich Institute of Biomedical Engineering (MIBE), Munich Institute of Integrated Materials, Energy and Process Engineering (MEP), Department of Electrical Engineering, School of Computation, Information and Technology (CIT), Technical University of Munich (TUM) Einsteinstraße 25 Munich 81675 Germany ghulam.destgeer@tum.de.ORCID https://orcid.org/0000-0002-3745-0254
Morteza Hasanzadeh KafshgariHeinz-Nixdorf-Chair of Biomedical Electronics, TranslaTUM, MIBE, School of Computation, Information and Technology, Technical University of Munich Einsteinstraße 25 81675 Munich Germany.ORCID https://orcid.org/0000-0001-5202-8505
Ali Bashiri DezfouliDepartment of Otolaryngology, Head and Neck Surgery, TUM School of Medicine and Health, Technical University of Munich 81675 Munich Germany.ORCID https://orcid.org/0009-0003-1412-5349
Oliver HaydenHeinz-Nixdorf-Chair of Biomedical Electronics, TranslaTUM, MIBE, School of Computation, Information and Technology, Technical University of Munich Einsteinstraße 25 81675 Munich Germany.ORCID https://orcid.org/0000-0002-2678-8663
Gabriele MulthoffExperimental Radiation Oncology and Radiobiology, TranslaTUM, School of Medicine, Technical University of Munich Einsteinstraße 25 81675 Munich Germany.ORCID https://orcid.org/0000-0002-2616-3137
Ghulam DestgeerControl and Manipulation of Microscale Living Objects, Center for Translational Cancer Research (TranslaTUM), Munich Institute of Biomedical Engineering (MIBE), Munich Institute of Integrated Materials, Energy and Process Engineering (MEP), Department of Electrical Engineering, School of Computation, Information and Technology (CIT), Technical University of Munich (TUM) Einsteinstraße 25 Munich 81675 Germany ghulam.destgeer@tum.de.ORCID https://orcid.org/0000-0002-4498-1643

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune-cancer cell interactions play a central role in understanding antitumor responses and evaluating immunotherapies. However, long-term, single-cell-level analysis of these interactions remains challenging. To address this, we developed CellTrap, an instrument-free, perfusion-capable microfluidic device featuring 1024 parallel traps. Each trap is equipped with a filter constriction to stably retain cells under hydrostatic flow, sustain continuous medium perfusion, and minimize trap-to-trap crosstalk. By intentionally leveraging stochastic Poisson loading, a single seeding step simultaneously generates perfectly matched internal controls alongside variable effector-to-target (E : T) ratios across the array. Device characterization using 10 µm fluorescent beads and cells validated the predictable trap occupancy governed by Poisson statistics. Initial proof-of-concept experiments using primary human PBMCs against GFP-expressing U87 (U87

Identifiers

PMID41969376
PMCPMC13068002

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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.