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Weng L, Tang WS, Wang X, Gong Y, Liu C, Hong NN, Tao Y, Li KZ, Liu SN, Jiang W, Li Y, Yao K, Chen L, Huang H, Zhao YZ, Hu ZP, Lu Y, Ye H, Du X, Zhou H, Li P, Zhao TJ. Surplus fatty acid synthesis increases oxidative stress in adipocytes and lnduces lipodystrophy. Nat Commun 2024; 15:133. [PMID: 38168040 PMCID: PMC10761979 DOI: 10.1038/s41467-023-44393-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 12/12/2023] [Indexed: 01/05/2024] Open
Abstract
Adipocytes are the primary sites for fatty acid storage, but the synthesis rate of fatty acids is very low. The physiological significance of this phenomenon remains unclear. Here, we show that surplus fatty acid synthesis in adipocytes induces necroptosis and lipodystrophy. Transcriptional activation of FASN elevates fatty acid synthesis, but decreases NADPH level and increases ROS production, which ultimately leads to adipocyte necroptosis. We identify MED20, a subunit of the Mediator complex, as a negative regulator of FASN transcription. Adipocyte-specific male Med20 knockout mice progressively develop lipodystrophy, which is reversed by scavenging ROS. Further, in a murine model of HIV-associated lipodystrophy and a human patient with acquired lipodystrophy, ROS neutralization significantly improves metabolic disorders, indicating a causal role of ROS in disease onset. Our study well explains the low fatty acid synthesis rate in adipocytes, and sheds light on the management of acquired lipodystrophy.
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Affiliation(s)
- Li Weng
- State Key Laboratory of Genetic Engineering, Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism and Integrative Biology, Drug Clinical Trial Center, Shanghai Xuhui Central Hospital / Zhongshan-Xuhui Hospital, Zhongshan Hospital, Fudan University, Shanghai, China
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Wen-Shuai Tang
- State Key Laboratory of Genetic Engineering, Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism and Integrative Biology, Drug Clinical Trial Center, Shanghai Xuhui Central Hospital / Zhongshan-Xuhui Hospital, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xu Wang
- School of Life Science, Anhui Medical University, Research Center for Translational Medicine, the Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yingyun Gong
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Changqin Liu
- Department of Endocrinology and Diabetes, the First Affiliated Hospital, Xiamen University, Xiamen, Fujian, China
| | - Ni-Na Hong
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, China
| | - Ying Tao
- State Key Laboratory of Genetic Engineering, Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism and Integrative Biology, Drug Clinical Trial Center, Shanghai Xuhui Central Hospital / Zhongshan-Xuhui Hospital, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Kuang-Zheng Li
- State Key Laboratory of Genetic Engineering, Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism and Integrative Biology, Drug Clinical Trial Center, Shanghai Xuhui Central Hospital / Zhongshan-Xuhui Hospital, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Shu-Ning Liu
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China
| | - Wanzi Jiang
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ying Li
- Department of Endocrinology, Northern Jiangsu People's Hospital, Yangzhou, Jiangsu, China
| | - Ke Yao
- School of Pharmaceutical Sciences, Tsinghua-Peking Joint Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, China
| | - Li Chen
- State Key Laboratory of Genetic Engineering, Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism and Integrative Biology, Drug Clinical Trial Center, Shanghai Xuhui Central Hospital / Zhongshan-Xuhui Hospital, Zhongshan Hospital, Fudan University, Shanghai, China
| | - He Huang
- State Key Laboratory of Genetic Engineering, Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism and Integrative Biology, Drug Clinical Trial Center, Shanghai Xuhui Central Hospital / Zhongshan-Xuhui Hospital, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yu-Zheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China
| | - Ze-Ping Hu
- School of Pharmaceutical Sciences, Tsinghua-Peking Joint Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Tsinghua University, Beijing, China
| | - Youli Lu
- Shanghai Engineering Research Center of Phase I Clinical Research & Quality Consistency Evaluation for Drugs, Institute of Clinical Mass Spectrometry, Shanghai Academy of Experimental Medicine, Shanghai, China
| | - Haobin Ye
- State Key Laboratory of Genetic Engineering, Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism and Integrative Biology, Drug Clinical Trial Center, Shanghai Xuhui Central Hospital / Zhongshan-Xuhui Hospital, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xingrong Du
- State Key Laboratory of Genetic Engineering, Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism and Integrative Biology, Drug Clinical Trial Center, Shanghai Xuhui Central Hospital / Zhongshan-Xuhui Hospital, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hongwen Zhou
- Department of Endocrinology and Metabolism, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
| | - Peng Li
- State Key Laboratory of Genetic Engineering, Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism and Integrative Biology, Drug Clinical Trial Center, Shanghai Xuhui Central Hospital / Zhongshan-Xuhui Hospital, Zhongshan Hospital, Fudan University, Shanghai, China.
- Tianjian Laboratory of Advanced Biomedical Sciences, School of life sciences, Zhengzhou University, Zhengzhou, Henan, China.
| | - Tong-Jin Zhao
- State Key Laboratory of Genetic Engineering, Shanghai Key Laboratory of Metabolic Remodeling and Health, Institute of Metabolism and Integrative Biology, Drug Clinical Trial Center, Shanghai Xuhui Central Hospital / Zhongshan-Xuhui Hospital, Zhongshan Hospital, Fudan University, Shanghai, China.
- Tianjian Laboratory of Advanced Biomedical Sciences, School of life sciences, Zhengzhou University, Zhengzhou, Henan, China.
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Li KZ, Huang QY, Tong KJ, Wang LW, Gou WB. [Imaging analysis of primary hepatic adenosquamous cell carcinoma: a case report]. Zhonghua Gan Zang Bing Za Zhi 2023; 31:643-645. [PMID: 37400391 DOI: 10.3760/cma.j.cn501113-20220531-00291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Subscribe] [Scholar Register] [Indexed: 07/05/2023]
Affiliation(s)
- K Z Li
- Department of Imaging, People's Hospital of Wanning City, Hainan Province, Wanning 571500, China
| | - Q Y Huang
- Chongqing Medical University Medical Imaging Specialty, Chongqing 400000, China
| | - K J Tong
- Department of Imaging, People's Hospital of Wanning City, Hainan Province, Wanning 571500, China
| | - L W Wang
- Department of Imaging, People's Hospital of Wanning City, Hainan Province, Wanning 571500, China
| | - W B Gou
- Department of Imaging, People's Hospital of Wanning City, Hainan Province, Wanning 571500, China
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Cheong KX, Lim LW, Li KZ, Tan CS. A novel and faster method of manual grading to measure choroidal thickness using optical coherence tomography. Eye (Lond) 2017; 32:433-438. [PMID: 29052608 DOI: 10.1038/eye.2017.210] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2016] [Accepted: 07/05/2017] [Indexed: 11/09/2022] Open
Abstract
PurposeChoroidal thickness (CT) measurements are typically obtained from manual segmentation of optical coherence tomography (OCT) B-scans. This method is time-consuming. We aimed to describe a novel and faster technique to obtain CT measurements.Patients and methodsIn a prospective cohort study of 200 healthy eyes, Spectral-Domain OCT with enhanced depth imaging were performed with the Spectralis OCT using standardised imaging protocols. The OCT scans were independently graded by reading centre-certified graders. The standard method of manual adjustment of segmentation boundaries was performed. The new method consisted of adjusting the lower segmentation line to the choroid-scleral boundary to generate the combined choroid-retina thickness, and subtracting the original retinal thickness (RT) from it to measure CT. Mean CT in the respective Early Treatment Diabetic Retinopathy Study (ETDRS) subfields was measured via the two methods, and were compared with intraclass correlation coefficients (ICC) and Bland-Altman plots.ResultsThe mean central subfield CT was 324.4 μm using the original method, compared with 328.8 μm using the new method, with a mean difference of 4.5 μm (range: -14.0 to +4.0 μm; P<0.001), and ICC for agreement of 0.9996 (P<0.001). Similar comparability was achieved for mean CT across other ETDRS subfields, with mean differences ranging from 2.4 to 3.7 μm, and ICCs ranging from 0.9993 to 0.9995 (all P<0.001).ConclusionsMean CT can be measured by subtracting the original RT from the combined choroid-retina thickness. Only one segmentation line needs to be adjusted, instead of two, reducing time required for segmentation. This method is faster and reliable.
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Affiliation(s)
- K X Cheong
- National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore, Singapore
| | - L W Lim
- National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore, Singapore
| | - K Z Li
- National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore, Singapore
| | - C S Tan
- National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore, Singapore.,Fundus Image Reading Center, National Healthcare Group Eye Institute, Singapore, Singapore
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Abstract
We investigated the regulation of sequential action using a new paradigm. Participants learned a sequence of seven stimulus categories and then monitored for them during successive displays. All displays were instances of these categories, presented in pseudorandom order. On each trial, participants monitored for an instance of Category 1, pressed a key on a computer keyboard, then monitored for an instance of Category 2, pressed a key on the keyboard, and so on for all seven categories. Thus, a perfect trial contained exactly seven responses. Intrusion errors were classified as a function of ordinal distance from the current serial position (n). Fewer intrusion errors were made at near serial positions than at far ones, suggesting a gradient of lateral inhibition. In addition, more intrusions were made on n + 1 categories than n - 1 categories, suggesting greater availability of intended than completed goals. In accord with current models of sequential action, the results indicate lateral and self-inhibition as important mechanisms in regulation of sequential action.
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Affiliation(s)
- K Z Li
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Lentzeallee 94, D-14195, Berlin, Germany.
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Abstract
Two studies assessed the presence of a synchrony effect between peak circadian arousal and time of testing for both older and younger adults. Participants performed a reading aloud task that included distracting words that were either present or absent and, if present, were either thematically related or unrelated to the target text. As well, the distracting material was presented in either spatially predictable or unpredictable locations. In each experiment, older and younger adults were tested at optimal versus nonoptimal times. Both experiments showed age differences in susceptibility to distraction, replicating earlier findings (e.g., M. C. Carlson, L. Hasher, R. T. Zacks, & S. L. Connelly, 1995). Neither showed differences due to time of testing, suggesting a boundary condition for cognitive disruptions associated with circadian arousal patterns.
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Affiliation(s)
- K Z Li
- Department of Psychology, Duke University, Durham, North Carolina 27708, USA.
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