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| 1 | Antioxidant activitiesand antioxidative components in the surf clam, Mactra veneriformis显示文摘 | LUAN Hemi WANG Lingchong WU Hao | 2011 | Natural Product Research2011，25，1920： | 1 |
| 2 | Machine Learning for Investigation on Endocrine-Disrupting Chemicals with Gestational Age and Delivery Time in a Longitudinal Cohort显示文摘Endocrine-disrupting chemicals(EDCs)are widespread environmental chemicals that are often considered as risk factors with weak activity on the hormone-dependent process of pregnancy.However,the adverse effects of EDCs in the body of pregnant women were underestimated.The interaction between dynamic concentration of EDCs and endogenous hormones(EHs)on gestational age and delivery time remains unclear.To define a temporal interaction between the EDCs and EHs during pregnancy,comprehensive,unbiased,and quantitative analyses of 33 EDCs and 14 EHs were performed for a longitudinal cohort with 2317 pregnant women.We developed a machine learning model with the dynamic concentration information of EDCs and EHs to predict gestational age with high accuracy in the longitudinal cohort of pregnant women.The optimal combination of EHs and EDCs can identify when labor occurs(time to delivery within two and four weeks,AUROC of 0.82).Our results revealed that the bisphenols and phthalates are more potent than partial EHs for gestational age or delivery time.This study represents the use of machine learning methods for quantitative analysis of pregnancy-related EDCs and EHs for understanding the EDCs’mixture effect on pregnancy with potential clinical utilities. | Hemi Luan Hongzhi Zhao Jiufeng Li Yanqiu Zhou Jing Fang Hongxiu Liu Yuanyuan Li Wei Xia Shunqing Xu Zongwei Cai | 2021 | Research2021，，1： | 0 |
| 3 | MS‑Based Metabolomics for the Investigation of Neuro‑Metabolic Changes Associated with BDE‑47 Exposure in C57BL/6 Mice显示文摘Polybrominated diphenyl ethers(PBDE),as one kind of the major persistent organic pollutants(POP),have potential adverse effects on human health.2,2′,4,4′-tetrabromodiphenyl ether(BDE-47)has been identified as one of the dominant PBDE congener in environmental and human samples.In this paper,liquid chromatography–orbitrap mass spectrometry(LC-Orbitrap MS)was applied for the profiling analysis of small metabolites in mice serum and striatum.The metabolic characteristics of adult male C57BL/6 mice exposed to BDE-47 were investigated with a non-targeted metabolomics method.The partial least-squares discriminant analysis(PLS-DA)indicated that the metabolites profile was significantly changed due to the exposure.Fiftyseven differential metabolites that significantly altered in mice serum and striatum were identified through databases searching and authentic standards confirmation.The related metabolic pathways mainly involved purine metabolism,alanine,aspartate and glutamate metabolism,tryptophan metabolism,phenylalanine metabolism,and glutathione metabolism.On the basis of metabolic variations,molecular mechanisms including disturbance of dopaminergic system,neurotransmitters regulation,DNA methylation,and oxidative stress were proposed.The obtained results suggested that LC-Orbitrap MS-based metabolomics had the great potential for molecular understanding of metabolic regulation linked to the exposure of environment pollutants. | Fenfen Ji Hemi Luan Yingyu Huang Zongwei Cai Min Li | 2017 | Journal of Analysis and Testing2017，1，3： | 0 |
| 4 | Machine Learning for Investigation on Endocrine-Disrupting Chemicals with Gestational Age and Delivery Time in a Longitudinal Cohort显示文摘Endocrine-disrupting chemicals(EDCs)are widespread environmental chemicals that are often considered as risk factors with weak activity on the hormone-dependent process of pregnancy.However,the adverse effects of EDCs in the body of pregnant women were underestimated.The interaction between dynamic concentration of EDCs and endogenous hormones(EHs)on gestational age and delivery time remains unclear.To define a temporal interaction between the EDCs and EHs during pregnancy,comprehensive,unbiased,and quantitative analyses of 33 EDCs and 14 EHs were performed for a longitudinal cohort with 2317 pregnant women.We developed a machine learning model with the dynamic concentration information of EDCs and EHs to predict gestational age with high accuracy in the longitudinal cohort of pregnant women.The optimal combination of EHs and EDCs can identify when labor occurs(time to delivery within two and four weeks,AUROC of 0.82).Our results revealed that the bisphenols and phthalates are more potent than partial EHs for gestational age or delivery time.This study represents the use of machine learning methods for quantitative analysis of pregnancy-related EDCs and EHs for understanding the EDCs’mixture effect on pregnancy with potential clinical utilities. | Hemi Luan Hongzhi Zhao Jiufeng Li Yanqiu Zhou Jing Fang Hongxiu Liu Yuanyuan Li Wei Xia Shunqing Xu Zongwei Cai | 2022 | Research2022，，1： | 0 |
| 5 | Urine biomarkers discovery by metabolomics and machine learning for Parkinson’s disease diagnoses显示文摘Parkinson’s disease(PD)is a complex neurological disorder that typically worsens with age.A wide range of pathologies makes PD a very heterogeneous condition,and there are currently no reliable diagnostic tests for this disease.The application of metabolomics to the study of PD has the potential to identify disease biomarkers through the systematic evaluation of metabolites.In this study,urine metabolic profiles of 215 urine samples from 104 PD patients and 111 healthy individuals were assessed based on liquid chromatography-mass spectrometry.The urine metabolic profile was first evaluated with partial leastsquares discriminant analysis,and then we integrated the metabolomic data with ensemble machine learning techniques using the voting strategy to achieve better predictive performance.A combination of 8-metabolite predictive panel performed well with an accuracy of over 90.7%.Compared to control subjects,PD patients had higher levels of 3-methoxytyramine,N-acetyl-l-tyrosine,orotic acid,uric acid,vanillic acid,and xanthine,and lower levels of 3,3-dimethylglutaric acid and imidazolelactic acid in their urine.The multi-metabolite prediction model developed in this study can serve as an initial point for future clinical studies. | Xiaoxiao Wang Xinran Hao Jie Yan Ji Xu Dandan Hu Fenfen Ji Ting Zeng Fuyue Wang Bolun Wang Jiacheng Fang Jing Ji Hemi Luan Yanjun Hong Yanhao Zhang Jinyao Chen Min Li Zhu Yang Doudou Zhang Wenlan Liu Xiaodong Cai Zongwei Cai | 2023 | Chinese Chemical Letters2023，34，10： | 0 |
| 6 | Association of altered serum acylcarnitine levels in early pregnancy and risk of gestational diabetes mellitus显示文摘Gestational diabetes mellitus(GDM)is a high-prevalence disease and diagnosed in middle pregnancy.Acylcarnitines are a series of fatty acid esters of carnitine and play important roles in fatty acid and carbohydrate metabolism.However,the role of acylcarnitine on the development of GDM remains unclear.This case-control study involving 214 study participants(107 GDM cases and 107 matched controls)was conducted in a cohort,in China,from 2013 to 2015.The levels of carnitine and 36 acylcarnitines in serum samples collected at the early stage of pregnancy were determined by using ultra-high performance liquid chromatography coupled with tandem mass spectrometry.The associations of the levels of the 37 targeted compounds with GDM risk were investigated by using binary conditional logistic regression models.Alterations in acylcarnitine levels were observed 9–17 weeks before GDM diagnosis.The increases in levels of propionyl-carnitine,malonyl-carnitine,isovaleryl-carnitine,palmitoyl-carnitine and linoleoyl-carnitine were associated with GDM risk with odds ratios(ORs)per standard deviation(SD)increment greater than 1(p<0.05),after adjustment for potential confounding factors(pre-pregnancy body mass index and parity).On the contrary,the increases of decanoyl-carnitine,decenoyl-carnitine,tetradecenoyl-carnitine,tetradecandienoylcarnitine levels were associated with the reduced risk for GDM(ORs per SD<1,p<0.05).To our knowledge,the present study is the largest case-control study to investigate the association between early-pregnancy acylcarnitine levels in serum and GDM risk.The findings add to the evidence for the association between acylcarnitine levels and GDM risk. | Hongzhi Zhao Han Li Yuanyuan Zheng Lin Zhu Jing Fang Li Xiang Shunqing Xu Yanqiu Zhou Hemi Luan Wei Xia Zongwei Cai | 2020 | Science China Chemistry2020，63，1： | 0 |
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