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The novel nano-selenium supplement extends lifespan and delays multi-organs aging by regulating the Sik1 pathway through maintaining calcium homeostasis

GSE303490 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/07/12 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.
Summary (written by the submitters)
Aging involves progressive physiological decline and increased disease susceptibility, creating demand for effective interventions. While selenium regulates redox homeostasis and aging, its therapeutic use is limited by bioavailability and toxicity. We developed diselenide-bridged mesoporous silica nanoparticles (SeMSNs) as a novel delivery system.
Read the full summary ↓
SeMSNs delayed cellular senescence in fibroblasts and H₂O₂-induced models by reducing oxidative stress and senescence markers (p16, p21). In aged mice, SeMSNs extended lifespan, reduced frailty, and improved multiple age-related conditions including muscle atrophy, renal dysfunction, cognitive decline, and hepatic steatosis while restoring metabolic balance. Mechanistically, SeMSNs upregulated selenoproteins (GPx1, SelK), restored calcium homeostasis, attenuated ER stress, and inhibited NFATc2-mediated Sik1 transcription. Clinical data showed inverse correlations between selenium levels and aging biomarkers. SeMSNs also rejuvenated human adipose progenitor cells via calcium-NFATc2-Sik1 modulation. These findings reveal SeMSNs surpass conventional antioxidants by targeting selenium-calcium crosstalk, providing a translatable nanotherapeutic strategy for multi-organs aging intervention and healthy longevity through selenium's molecular mechanisms.
This dataset
Open GSE303490 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 GSE303490_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 PRJNA1295520 and SRA study SRP603064. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
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

Search all mouse 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.