Evidence map›Paper›PMID 39415954›Full record

ArticleFrontiers in veterinary science2024

Transcriptome analysis provides new insights into the response of canine intestinal epithelial cells treated by sulforaphane: a natural product of cruciferous origin.

Kaiqi Li, Jin Yan, Shiqi Wang, Chuyang Zhu, Qi Zhu, Sichen Lu, Ping Hu, Tadelle Dessie, In Ho Kim, Abdelkareem A Ahmed and 3 more

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Kaiqi LiLaboratory of Animal Physiology and Molecular Nutrition, Jiangsu Key Laboratory of Animal Genetic Breeding and Molecular Design, College of Animal Science and Technology, Yangzhou University, Yangzhou, China.
Jin YanLaboratory of Animal Physiology and Molecular Nutrition, Jiangsu Key Laboratory of Animal Genetic Breeding and Molecular Design, College of Animal Science and Technology, Yangzhou University, Yangzhou, China.
Shiqi WangLaboratory of Animal Physiology and Molecular Nutrition, Jiangsu Key Laboratory of Animal Genetic Breeding and Molecular Design, College of Animal Science and Technology, Yangzhou University, Yangzhou, China.
Chuyang ZhuLaboratory of Animal Physiology and Molecular Nutrition, Jiangsu Key Laboratory of Animal Genetic Breeding and Molecular Design, College of Animal Science and Technology, Yangzhou University, Yangzhou, China.
Qi ZhuLaboratory of Animal Physiology and Molecular Nutrition, Jiangsu Key Laboratory of Animal Genetic Breeding and Molecular Design, College of Animal Science and Technology, Yangzhou University, Yangzhou, China.
Sichen LuLaboratory of Animal Physiology and Molecular Nutrition, Jiangsu Key Laboratory of Animal Genetic Breeding and Molecular Design, College of Animal Science and Technology, Yangzhou University, Yangzhou, China.
Ping HuLaboratory of Animal Physiology and Molecular Nutrition, Jiangsu Key Laboratory of Animal Genetic Breeding and Molecular Design, College of Animal Science and Technology, Yangzhou University, Yangzhou, China.
Tadelle DessieInternational Livestock Research Institute, Addis Ababa, Ethiopia.
In Ho KimDepartment of Animal Resource and Science, Dankook University, Cheonan, Republic of Korea.
Abdelkareem A AhmedDepartment of Veterinary Biomedical Sciences, Botswana University of Agriculture and Agriculture and Natural Resources, Gaborone, Botswana.
Hao-Yu LiuLaboratory of Animal Physiology and Molecular Nutrition, Jiangsu Key Laboratory of Animal Genetic Breeding and Molecular Design, College of Animal Science and Technology, Yangzhou University, Yangzhou, China.
Wael EnnabLaboratory of Animal Physiology and Molecular Nutrition, Jiangsu Key Laboratory of Animal Genetic Breeding and Molecular Design, College of Animal Science and Technology, Yangzhou University, Yangzhou, China.
Demin CaiLaboratory of Animal Physiology and Molecular Nutrition, Jiangsu Key Laboratory of Animal Genetic Breeding and Molecular Design, College of Animal Science and Technology, Yangzhou University, Yangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents a comprehensive transcriptome analysis of canine intestinal epithelial cells following treatment with sulforaphane (SFN), a naturally occurring compound found in cruciferous vegetables with established anti-inflammatory and antioxidant properties. Through high-throughput sequencing, we identified 29,993 genes, among which 1,612 were differentially expressed, with 792 up-regulated and 820 down-regulated in response to SFN treatment. Our analysis revealed significant enrichment of genes in pathways associated with the inflammatory response, lipid metabolism, oxidative stress response, and T-cell mediated immunity, suggesting SFN's potential in modulating these biological processes. Notably, the PPARγ gene, which plays a crucial role in the body's oxidative stress and inflammatory response, was highly up-regulated, indicating its possible centrality in SFN's effects. Gene-gene interaction analysis further supported SFN's role in alleviating inflammation through PPARγ, with key genes in oxidative stress and inflammatory response pathways showing significant correlations with PPARγ. Overall, our findings provide molecular evidence for SFN's protective effects on canine intestinal health, potentially through the modulation of inflammatory and oxidative stress pathways, with PPARγ emerging as a critical mediator.

Indexed as

canineinflammation responseintestinesulforaphanetranscriptome analysis

Identifiers

PMID39415954
PMCPMC11479859

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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.