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Multi-organ immunity on a 3D-printed multi-tissue chip with tubing-free impeller pump

GSE268137 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2024/12/19 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 18 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
18 samples: 18 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
A 3D-printed multi-compartment organ-on-chip platform with a tubing-free pump models communication with the lymph nodeLab on a chip · 2025
Summary (written by the submitters)
Multi-organ-on-chip systems (MOOCs) have the potential to mimic communication between organ systems and reveal mechanisms of health and disease. However, many existing MOOCs are challenging for non-experts to implement, due to complex tubing, electronics, or pump mechanisms. In addition, few MOOCs have incorporated immune organs such as the lymph node (LN), limiting their applicability to critical events such as vaccination.
Read the full summary ↓
Here we developed a 3D-printed, user-friendly device and companion tubing-free impeller pump to co-culture two or more tissue samples, including a LN, under a recirculating common media. Native tissue structure and immune function were incorporated by maintaining slices of murine LN tissue ex vivo in 3Dprinted mesh supports for at least 24 hr. In a two-compartment model of a LN and an upstream injection site, vaccination of the multi-tissue chip was similar to in vivo vaccination in terms of locations of antigen accumulation and acute changes in activation markers and gene expression in the LN. We anticipate that in the future, this flexible platform will enable models of multi-organ immune responses throughout the body.
Published in
A 3D-printed multi-compartment organ-on-chip platform with a tubing-free pump models communication with the lymph node
Cook SR, Ball AG, Mohammad A et al. · Lab on a chip 2025 · PMID 39661075 · doi:10.1039/d4lc00489b
This dataset
Open GSE268137 in finder → Find more mouse RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE268137_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1114743 and SRA study SRP509246. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39661075) ↗
Study design
18 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 18 sample titles: 18 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.