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Effects of Smoldering Eucalyptus Wood Smoke Extract on Primary Human Brain Microvascular Endothelial Cells (HBMEC) and Immortalized Human Cerebral Microvascular Endothelial Cell Line (hCMEC/D3)

GSE271935 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2024/10/02 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 48 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
Eucalyptus Wood Smoke Extract Elicits a Dose-Dependent Effect in Brain Endothelial CellsInternational journal of molecular sciences · 2024
Summary (written by the submitters)
Increase in frequency and size of wildfire raises a significant public health concern due to rapid climate change. Epidemiological studies have shown that wildfire smoke exposure can increase the risk of neurological disorders. Our study aims to understand how wildfire smoke particles affect brain endothelial cells using both primary human brain microvascular endothelial cells (HBMEC) and an immortalized human cerebral microvascular endothelial cell line (hCMEC/D3).
Read the full summary ↓
HBMEC and hCMEC/D3 were exposed to different levels of smoldering eucalyptus smoke particles (10, 30, 50 ug/mL) for 24 hr. Supernatants were collected for LDH and ELISA array, cell lysates were collected for RNAseq, and cells were fixed and stained for tight junction marker (Zonula Occludens-1, ZO-1) via ICC. Our study found that treatment to smoldering eucalyptus particles can increase inflammatory cytokine production dose-dependently in HBMECs and hCMEC/D3. Moreover, RNAseq analyses resulted in dose-dependent changes in HBMEC and hCMEC/D3 from wood smoke treatment that could be mediated via AhR and Nrf2 pathways.
Published in
Eucalyptus Wood Smoke Extract Elicits a Dose-Dependent Effect in Brain Endothelial Cells
You DJ, Gorman BM, Goshi N et al. · International journal of molecular sciences 2024 · PMID 39408618 · doi:10.3390/ijms251910288
This dataset
Open GSE271935 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 GSE271935_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 PRJNA1134150 and SRA study SRP519110. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39408618) ↗
Study design
48 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 48 sample titles: 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.