ReviewAnimals : an open access journal from MDPI2022
Progress in Expression Pattern and Molecular Regulation Mechanism of LncRNA in Bovine Mastitis.
Review in Animals : an open access journal from MDPI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
- Long non-coding RNAs link DNA methylation to immune regulatory networks in bovine subclinical mastitis.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- Transcriptome-derived variants in milk reveal host response signatures to subclinical intramammary infection in Holstein cattle.Journal of animal science and biotechnology · 2026Article
- Palmatine Attenuates LPS-Induced EMT in MAC-T Cells and Mammary Fibrosis in Mice, with Suppression of NF-κB/TGF-β1/Smad Signaling In Vivo.Animals : an open access journal from MDPI · 2026Article
- Bovine Mastitis-DerivedVeterinary sciences · 2025Article
- Skeletal muscle lncRNA profile associated with fatty acids in Nellore beef cattle.Scientific reports · 2025Article
- Article
- Profiling the full-length transcriptome of plasma cell mastitis via nanopore sequencing.BMC genomic data · 2025Article
- Integrated co-expression analysis of regulatory elements (miRNA, lncRNA, and TFs) in bovine monocytes induced by Str. uberis.Scientific reports · 2023Article
- Identification of long non-coding RNA-mRNA interactions and genome-wide lncRNA annotation in animal transcriptome profiling.Journal of animal science and technology · 2023Review
- Role of Long Noncoding RNAs in the Regulation of Cellular Immune Response and Inflammatory Diseases.Cells · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Bovine mastitis is an inflammatory disease caused by pathogenic microbial infection, trauma, or other factors. Its morbidity is high, and it is difficult to cure, causing great harm to the health of cows and the safety of dairy products. Susceptibility or resistance to mastitis in individual cows is mainly determined by genetic factors, including coding genes and non-coding genes. Long non-coding RNAs (lncRNAs) are a class of endogenous non-coding RNA molecules with a length of more than 200 nucleotides (nt) that have recently been discovered. They can regulate the immune response of humans and animals on three levels (transcription, epigenetic modification, and post-transcription), and are widely involved in the pathological process of inflammatory diseases. Over the past few years, extensive findings revealed basic roles of lncRNAs in inflammation, especially bovine mastitis. This paper reviews the expression pattern and mechanism of long non-coding RNA (lncRNA) in inflammatory diseases, emphasizes on the latest research progress of the lncRNA expression pattern and molecular regulatory mechanism in bovine mastitis, analyzes the molecular regulatory network of differentially expressed lncRNAs, and looks forward to the research and application prospect of lncRNA in bovine mastitis, laying a foundation for molecular breeding and the biological therapy of bovine mastitis.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.