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Cranial photoregulation reshapes brain border immunity and promotes recovery after stroke

GSE252774 Mus musculus (mouse) RNA-seq (gene expression) 27 samples Submitted 2024/04/18 Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 27 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
27 samples: 9 conditions, mostly in triplicateGroups 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.
Summary (written by the submitters)
The skull bone marrow represents a targetable neuroimmune interface adjacent to the brain borders with the potential to improve stroke outcomes. Here, we identified the skull as a highly responsive immune niche and developed a cranial photo-immunologic regulation (CPR) strategy using low-dose, narrow-band medical UVB. Targeted irradiation of the interparietal region reshapes brain border immune crosstalk, effectively promoting repair and functional recovery after ischemic injury.
Read the full summary ↓
Mechanistically, UVB-based CPR reverses stroke-induced suppression of meningeal B cell activation, contributing to restoring brain border immune homeostasis. Depletion of meningeal B cells further demonstrates that these cells are required for the therapeutic effects of CPR. These findings establish the skull as an actionable target for neuroimmune modulation along the skull–meninges–brain axis and provide a potentially transformative strategy for treating neurological disease.
This dataset
Open GSE252774 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 GSE252774_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 PRJNA1062428 and SRA study SRP482559. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
9 conditions, mostly in triplicate
NB ×3 NM ×3 NS ×3 UVB0 ×3 UVM0 ×3 UVS0 ×3 UVB1 ×3 UVM1 ×3 +1 more

Supports a between-group comparison across 27 samples.

How we read this: 9 replicated groups read from 27 sample titles; they account for 27 of them. 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.