Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1053507 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Microplastics (MPs) have become a serious global environmental threat that causes damage to mammalian organs. In this work, we investigated the potential molecular mechanism underlying the development of liver fibrosis induced by long-term exposure to three different sized PS-MPs (80 nm, 0.5 µm and 5 µm) in mice. Liver fibrosis levels were evaluated in mice after chronic exposure to PS-MPs. Liver inflammation was mainly increased in chronic exposure to 80 nm and 0.5 µm PS-MPs. Liver lipid deposition was significantly enhanced after PS-MP exposure. However, oxidative stress was not changed under PS-MP exposure. GO enrichment and KEGG pathway analyses revealed that the DEGs and shared DEGs were mainly enriched in the metabolism of lipids. The mRNA expression levels of genes related to fatty acid oxidation, synthesis and transport were dramatically induced by PS-MP exposure. Four hub genes, Acot3, Abcc3, Nr1i3 and Fmo2, were identified by CytoHubba analysis of shared DEGs. The mRNA expression levels of three hub genes, Acot3, Abcc3 and Nr1i3, were significantly augmented under chronic PS-MP exposure. Our results suggest that Acot3, Abcc3 and Nr1i3 are potential molecules involved in the development of liver fibrosis under chronic exposure to PS-MPs.
2025-01-23 | GSE245069 | GEO
Project description:Purpose: To study Nf1 regulated pathways in controlling juvenile satellite cells quiescence induction. Methods: We sequenced total mRNAs isolated from juvenile satellite cells FACS sorted from postnatal day 7 Control (Nf1flox/+ Myf5Cre+) and KO (Nf1flox/flox Myf5Cre+) mouse hindlimb skeletal muscle. Results: Our study suggests that Nf1 is required for maintaining the balance between quiescence induction and amplification / differentiation in the postnatal MP pool. Conclusions: The tumor suppressor Nf1 maintains the myogenic progenitor (MP) pool during postnatal muscle development.
2021-09-25 | GSE159021 | GEO
Project description:We sequenced complementary DNA created from white muscle messenger RNA in juvenile blue rockfish and performed a differential gene expression analysis to describe the fishes' responses to the global change-related stressors of high pCO2 (low pH) and hypoxia (low dissolved oxygen, DO). To examine gene expression over ecologically realistic timescales that emulate the duration of spring upwelling events in the California Current ecosystem, we collected and sequenced samples after 12 h, 24 h and two weeks of exposure to four treatments: control (pH≈8.0, pCO2≈400μatm, DO≈8 mg/L), high pCO2 (pH≈7.6, pCO2≈1200μatm, DO≈8 mg/L), hypoxic (pH≈8.0, pCO2≈400μatm, DO≈4 mg/L), and combined high pCO2/hypoxic (pH≈7.6, pCO2≈1200μatm, DO≈4 mg/L).
2019-09-30 | GSE129003 | GEO
Project description:We sequenced mRNA from 9 liver samples of juvenile largemouth bass (Micropterus salmoides) taken from different lead concentration exposure treatment fish and control fish to investigate the transcriptome and comparative expression profiles of largemouth bass liver undergoing lead exposure.
2019-01-12 | GSE124986 | GEO
Project description:Skeletal muscle is a heterogeneous tissue consisting of blood vessels, connective tissue, and muscle fibers. The last are highly adaptive and can change their molecular composition depending on external and internal factors, such as exercise, age, and disease. Thus, examination of the skeletal muscles at the fiber type level is essential to detect potential alterations. Therefore, we established a protocol in which myosin heavy chain isoform immunolabeled muscle fibers were laser microdissected and separately investigated by mass spectrometry to develop advanced proteomic profiles of all murine skeletal muscle fiber types. Our in-depth mass spectrometric analysis revealed unique fiber type protein profiles, confirming fiber type-specific metabolic properties and revealing a more versatile function of type IIx fibers. Furthermore, we found that multiple myopathy-associated proteins were enriched in type I and IIa fibers. To further optimize the assignment of fiber types based on the protein profile, we developed a hypothesis-free machine-learning approach (available at: https://github.com/mpc-bioinformatics/FiPSPi), identified a discriminative peptide panel, and confirmed our panel using a public data set.
2021-06-07 | PXD025359 | Pride