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Authors
Cai, Ze-Rong
Wang, Wen https://orcid.org/0000-0003-0986-8853
Chen, Di
Chen, Hao-Jie https://orcid.org/0000-0002-4142-9829
Hu, Yan https://orcid.org/0000-0001-7208-1952
Luo, Xiao-Jing
Wang, Yi-Ting
Pan, Yi-Qian
Mo, Hai-Yu
Luo, Shu-Yu
Liao, Kun
Zeng, Zhao-Lei https://orcid.org/0000-0003-4420-5625
Li, Shan-Shan
Guan, Xin-Yuan
Fan, Xin-Juan
Piao, Hai-long https://orcid.org/0000-0001-7451-0386
Xu, Rui-Hua https://orcid.org/0000-0001-9771-8534
Ju, Huai-Qiang https://orcid.org/0000-0003-1713-5465
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Funding
Funding for this research was provided by:
MOST | National Key Research and Development Program of China (2022yfa1105300)
MOST | National Natural Science Foundation of China (82341010; 82273241; 8197625; 82103643; 32201217;)
Guangdong Basic and Applied Basic Research Foundation (2023B1515040030)
Liaoning Revitalization Talents Program (XLYC2002035)
深圳市科技创新委员会 | Sanming Project of Medicine in Shenzen Municipality (SZSM202211017)
Young Talents Program of Sun Yat-sen University Cancer Center (YTP-SYSUCC-0019)
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Article History
Received: 2 August 2024
Revised: 23 October 2024
Accepted: 25 October 2024
First Online: 14 November 2024
Disclosure and competing interests statement
: The authors declare no competing interests. The authors have applied for patents for the use of the serum lipid metabolic signature to diagnose and predict biosamples.
