Jing Li

Minzu University of China

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Hong Ding

Wuhan University

Xiao‐Long Yang

Ningxia Medical University

Tao Ban

Harbin Medical University

Zhijie Sun

Huawei Technologies (United Kingdom)

Xuan He

Southwest Jiaotong University

Qizhu Tang

Renmin Hospital of Wuhan University

Chengyun Huang

Minzu University of China

Binfan Zheng

Huawei Technologies (United Kingdom)

Jing Tong

Wuhan University

Rongqian Zhao

Huawei Technologies (United Kingdom)

Cooperative Institutions

Harbin Medical University

Wuhan University

Ministry of Education of the People's Republic of China

Chinese Academy of Sciences

University of North Carolina at Chapel Hill

Ministry of Science ICT and Future Planning

Southern Medical University

Renmin Hospital of Wuhan University

Sichuan University

University of Chinese Academy of Sciences

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Advanced tools in marine natural drug discovery

Current Opinion in Biotechnology (2016)

Guojian Zhang Jing Li Tianjiao Zhu Qianqun Gu Dehai Li

Marine life

Marine conservation

10.1016/j.copbio.2016.02.021

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Citations (53)

Caffeic acid phenethyl ester attenuates pathological cardiac hypertrophy by regulation of MEK/ERK signaling pathway in vivo and vitro

Life Sciences (2017)

Jie Ren Nan Zhang Hai‐Han Liao Si Chen Ling Xu

Pressure overload

10.1016/j.lfs.2017.04.016

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Citations (36)

Inhibitory effects of three Gn compounds on TNFα production by murine peritoneal macrophages.

Yaoxue xuebao (2000)

Jing Li Gui-Fang Cheng Zhu XiuYuan

Source

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Citations (2)

LocMoE: A Low-overhead MoE for Large Language Model Training

arXiv (Cornell University) (2024)

Jing Li Zhijie Sun Xuan He Li Zeng Yi Lin

The Mixtures-of-Experts (MoE) model is a widespread distributed and integrated learning method for large language models (LLM), which is favored due to its ability to sparsify and expand models efficiently. However, the performance of MoE is limited by load imbalance and high latency of All-To-All communication, along with relatively redundant computation owing to large expert capacity. Load imbalance may result from existing routing policies that consistently tend to select certain experts. The frequent inter-node communication in the All-To-All procedure also significantly prolongs the training time. To alleviate the above performance problems, we propose a novel routing strategy that combines load balance and locality by converting partial inter-node communication to that of intra-node. Notably, we elucidate that there is a minimum threshold for expert capacity, calculated through the maximal angular deviation between the gating weights of the experts and the assigned tokens. We port these modifications on the PanGu-Sigma model based on the MindSpore framework with multi-level routing and conduct experiments on Ascend clusters. The experiment results demonstrate that the proposed LocMoE reduces training time per epoch by 12.68% to 22.24% compared to classical routers, such as hash router and switch router, without impacting the model accuracy.

10.48550/arxiv.2401.13920

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Identification and validation of genes associated with aging‐related cardiovascular disease

The FASEB Journal (2024)

Jing Li Shengping Jiang Chengyun Huang Baihui Lu Xiao‐Long Yang

Abstract Aging is acknowledged as the most significant risk factor for cardiovascular disease (CVD). This study sought to identify and validate potential aging‐related genes associated with CVD by using bioinformatics. The confluence of the limma test, weighted correlation network analysis (WGCNA), and 2129 aging and senescence‐associated genes led to the identification of aging‐related differential expression genes (ARDEGs). By using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), potential biological roles and pathways of ARDEGs were identified. To find the significantly different functions between CVD and non‐cardiovascular disease (nCVD) and to reckon the processes score, enrichment analysis of all genes was carried out using gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). By using GO and KEGG, potential biological roles and pathways of ARDEGs were identified. To evaluate the immune cell composition of the immune microenvironment, we performed an immune infiltration analysis on the dataset from the training group. We were able to acquire four ARDEGs (PTGS2, MMP9, HBEGF, and FN1). Aging, cellular senescence, and nitric oxide signal transduction were selected for biological function analysis. The diagnostic value of the four ARDEGs in distinguishing CVD from nCVD samples was deemed to be favorable. This research identified four ARDEGs that are associated with CVD. This study provides insight into prospective novel biomarkers for aging‐related CVD diagnosis and progression monitoring.

KEGG

Senescence

Biological pathway

10.1096/fj.202301270rr

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Transient receptor potential melastatin 4 contributes to early-stage endothelial injury induced by arsenic trioxide

Toxicology Letters (2019)

Chunxiao Yu Yuyao Zhang Xia‐Yang Wu Haixia Tang Xueqi Liang

Viability assay

MTT assay

10.1016/j.toxlet.2019.04.035

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Citations (15)

Apigenin analogs as α-glucosidase inhibitors with antidiabetic activity

Bioorganic Chemistry (2023)

Honghui Liu Puxin Huang Xingchen Wang Yufang Ma Jing Tong

Docking (animal)

10.1016/j.bioorg.2023.107059

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Citations (5)

Atraric Acid Ameliorates Hyperpigmentation through the Downregulation of the PKA/CREB/MITF Signaling Pathway

International Journal of Molecular Sciences (2022)

Jing Li Shengping Jiang Chengyun Huang Xiao‐Long Yang

Atraric acid (AA) is derived from lichens and is widely used in perfumes for its desirable scent. It has been reported as having anti-inflammatory and antioxidant activity. Hyperpigmentation is the underlying cause of a variety of dermatological diseases that have a significant impact on patients' quality of life and are frequently difficult to treat. This study aimed to explore the inhibitory effects of AA on hyperpigmentation in vitro and in vivo and its potential molecular mechanisms. The cytological results revealed that at a dose of 250 μM, AA may reduce melanin content and tyrosinase levels without causing cytotoxicity. Furthermore, the expression of melanocortin-1 receptor (MC1R), phosphorylated protein kinase A (pPKA) and phosphorylated cAMP response element binding protein (pCREB) were downregulated in AA-administrated cells. In vivo, histological analysis showed that AA could inhibit melanin production and tyrosinase activity, and 3% AA had the best activity, with almost no side effects. Furthermore, the results of Western blot analysis and RT-PCR suggested that AA may suppress the mRNA transcription of microphthalmia-associated transcription factor (MITF) protein and tyrosine protease by decreasing the expression of MC1R, consequently decreasing the phosphorylation of PKA and CREB. Finally, the MC1R inhibitor MSG606 verified the hypothesis that AA suppresses melanin formation by downregulating the PKA/CREB/MITF signaling pathway. Taken together, our study offers valuable information for the development of AA as a possible ingredient in skin-lightening cosmeceuticals and hyperpigmentation inhibitors.

Microphthalmia-associated transcription factor

Melanocortin 1 receptor

Skin hyperpigmentation

10.3390/ijms232415952

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Citations (6)

GWAS for Interleukin-1β levels in gingival crevicular fluid identifies IL37 variants in periodontal inflammation

Carolina Digital Repository (University of North Carolina at Chapel Hill) (2018)

S. Offenbacher Yue Jiao S.J. Kim J.T. Marchesan Kevin Moss

Genome-wide Association Study

Interleukin 1β

Gingival inflammation

10.17615/vj08-2d58

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In Silico Prediction of Cytochrome P450-Mediated Site of Metabolism (SOM)

Protein and Peptide Letters (2013)

Liu Xian Qiancheng Shen Jing Li Shanshan Li Cheng Luo

Drug metabolism is a major consideration for modifying drug clearance and also a primary source for drug metabolite- induced toxicity. Cytochromes P450 (CYPs) are the major enzymes involved in drug metabolism and bioactivation, accounting for almost 75% of the total drug metabolism. Predicting the sites of cytochrome P450-mediated metabolism of drug-like molecules using in silico methods would be highly beneficial and time efficient. An ideal system would enable researchers to make a confident elimination decision based purely on the structure of a new compound. In this review, several tools and models for predicting probable site of metabolism (SOM) have been compared and discussed. The methods are generally based on enzyme structure, ligand structure, and combined methods. Although all the methods have certain accuracy and considerable progress has been made, the results of the calculations still need careful inspection. Keywords: ADME, computational method, CYP, cytochrome P450, SOM, Drug metabolism, drug clearance, Cytochromes P450, bioactivation, ligand

ADME

10.2174/0929866511320030006

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Citations (8)