Evidence map›Paper›PMID 41127549›Full record

ArticleMaterials today. Bio2025

Acquisition, quality control, and architecture of a large image dataset as a tool for in silico cell biological research.

Nikita Konshin, Marta Garcia Valverde, Danila Solodennikov, Koen Minartz, Vlado Menkovski, Rosalinde Masereeuw, Shantanu Singh, Silvia M Mihăilă, Jan de Boer

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Materials today. Bio, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Nikita KonshinDepartment of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, the Netherlands.
Marta Garcia ValverdeDivision of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands.
Danila SolodennikovDepartment of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, the Netherlands.
Koen MinartzDepartment of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, the Netherlands.
Vlado MenkovskiDepartment of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, the Netherlands.
Rosalinde MasereeuwDivision of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands.
Shantanu SinghImaging Platform, Broad Institute of Harvard and MIT, Cambridge, MA, United States of America.
Silvia M MihăilăDivision of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands.
Jan de BoerDepartment of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a large-scale, standardized image dataset and analysis pipeline designed to enable in silico discovery of cell-material interactions. This resource paper introduces an open, FAIR-aligned framework for acquiring, curating, and analyzing high-content imaging data of kidney podocytes cultured on 2176 micro-topographical surfaces using the TopoChip platform. Our workflow includes automated imaging, tilt correction, object segmentation, and multi-tiered quality control, resulting in over 5500 morphological features for >1.2 million cells. Structured metadata, standardized file architectures, and ontological annotations ensure that the dataset is fully interoperable and ready for reuse. To illustrate its versatility, we provide examples of how this resource supports machine learning model development, reproducible benchmarking, and hypothesis testing in cell biology and biomaterials science. This dataset and accompanying tools are designed as a foundational reference for the community, enabling scalable, quantitative, and reproducible exploration of how microenvironments shape cell behavior.

Indexed as

DatasetFAIR dataHigh-content imagingMachine learningMicro-topographyMorphological fingerprintingPodocyteQuality controlTopoChip

Identifiers

PMID41127549
PMCPMC12538699

What Socratic 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 Socratic graph.