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Human Dental Pulp Stem Cell derived exosomes as effective biomaterials for anti-inflammation and regeneration in pulpitis

GSE295186 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2025/04/26 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 10 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
Homo sapiens (human)
Samples
10 samples: 3 × Exo vs 3 × Exo_OD vs 3 × LPSGroups 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 study investigates the effects of exosomes derived from human dental pulp stem cells (hDPC-Exos) on pulpitis, an inflammatory dental condition. The research demonstrates that hDPC-Exos exhibit significant anti-inflammatory and regenerative properties, making them effective biomaterials for treating pulpitis. Exosomes were shown to downregulate pro-inflammatory cytokines and chemokines, such as interleukin-1β and tumor necrosis factor-alpha, thus suppressing inflammation.
Read the full summary ↓
Additionally, hDPC-Exos promoted angiogenesis and odontogenesis, facilitating recovery and regeneration of pulp tissue. These effects were observed through various analyses, including RNA sequencing and histological evaluations in an in vitro pulpitis model and a rat model of pulpitis. The findings suggest that hDPC-Exos hold potential as a cell-free therapeutic approach for oral inflammation and tissue regeneration.
This dataset
Open GSE295186 in finder → Find more human 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 GSE295186_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 PRJNA1253670 and SRA study SRP580230. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × Exo vs 3 × Exo_OD vs 3 × LPS

Supports a between-group comparison across 9 samples.

How we read this: 3 replicated groups read from 10 sample titles; they account for 9 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.