ArticleJournal of proteome research2024
Proteomics and Metabolic Characteristics of Boar Seminal Plasma Extracellular Vesicles Reveal Biomarker Candidates Related to Sperm Motility.
Article in Journal of proteome research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed.
- Comprehensive metabolomic profiling of Angiostrongylus cantonensis across its life cycle reveals developmental and host-associated metabolic signatures.Infectious diseases of poverty · 2026Article
- Metabolomic profiling of goat seminal plasma: insights into sperm motility regulation.BMC veterinary research · 2026Article
- Effect of autophagy-related (Atg) protein 5 on mouse epididymal sperm maturation.Journal of assisted reproduction and genetics · 2026Article
- Lipidomic Landscapes of Cryopreserved Sperm from Alpine and Spanish-Creole Bucks.Animals : an open access journal from MDPI · 2025Article
- Seminal Plasma Extracellular Vesicles: Key Mediators of Intercellular Communication in Mammalian Reproductive Systems.Veterinary sciences · 2025Review
- Proteomic analysis reveals the difference between the spermatozoa of young and old Sus scrofa.Scientific reports · 2025Article
- Updating Research on Extracellular Vesicles of the Male Reproductive Tract in Farm Animals: A Systematic Review.Animals : an open access journal from MDPI · 2024Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although seminal plasma extracellular vesicles (SPEVs) play important roles in sperm function, little is known about their metabolite compositions and roles in sperm motility. Here, we performed metabolomics and proteomics analysis of boar SPEVs with high or low sperm motility to investigate specific biomarkers affecting sperm motility. In total, 140 proteins and 32 metabolites were obtained through differentially expressed analysis and weighted gene coexpression network analysis (WGCNA). Seven differentially expressed proteins (DEPs) (ADIRF, EPS8L1, PRCP, CD81, PTPRD, CSK, LOC100736569) and six differentially expressed metabolites (DEMs) (adenosine, beclomethasone, 1,2-benzenedicarboxylic acid, urea, 1-methyl-l-histidine, and palmitic acid) were also identified in WGCNA significant modules. Joint pathway analysis revealed that three DEPs (GART, ADCY7, and NTPCR) and two DEMs (urea and adenosine) were involved in purine metabolism. Our results suggested that there was significant correlation between proteins and metabolites, such as IL4I1 and urea (
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