
Xinrui Wang
Articles
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3 weeks ago |
mdpi.com | Xinrui Wang |Jie Li |Jing Li |Lan Luo
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Nov 21, 2024 |
mdpi.com | Liyuan Wang |Honglei Qu |Xinrui Wang |Tianqi Wang
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Oct 15, 2024 |
biorxiv.org | Bowen Yang |Xinrui Wang |Jun Li |Shuang G. Zhao
AbstractBackground: With advancements in sequencing and mass spectrometry technologies, multi-omics data can now be easily acquired for understanding complex biological systems. Nevertheless, substantial challenges remain in determining the association between gene-metabolite pairs due to the non-linear and multifactorial interactions within cellular networks.
Decreased Astrocytic CCL5 by MiR-324-5p Ameliorates Ischemic Stroke Injury via CCR5/ERK/CREB Pathway
Sep 3, 2024 |
biorxiv.org | Lili Wang |Xinrui Wang |Jingxiu Li |Keyuan Gao
AbstractFollowing ischemic stroke, Ccl5 mRNA expression increased, while miR-324-5p expression decreased in the peri-infract cortex of middle cerebral artery occlusion (MCAO) mice. However, the roles of CCL5 and miR-324-5p in stroke remain unclear.
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Jan 24, 2024 |
biorxiv.org | Bowen Yang |Xinrui Wang |Jun Li |Shuang G. Zhao
AbstractWith advancements in sequencing and mass spectrometry technologies, multi-omics data can now be easily acquired for understanding complex biological systems. Nevertheless, substantial challenges remain in determining the association between gene-metabolite pairs due to the complexity of cellular networks.
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