| 1. |
- Li, Nannan, et al.
(author)
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Phytolith and simulation evidence for precipitation-modulated vegetation dynamics along the East Asian monsoon margin
- 2022
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In: Palaeogeography, Palaeoclimatology, Palaeoecology. - : Elsevier BV. - 0031-0182. ; 590
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Journal article (peer-reviewed)abstract
- An improved understanding of past interactions between terrestrial vegetation and various forcings, such as climate change, human impact, and paleofire, is crucial for assessing impacts of future global change on terrestrial ecosystems. This study seeks to find the key factor or factors that have driven Holocene vegetation change along the East Asian monsoon margin. Several high-resolution pollen records are reviewed and new phytolith-based paleovegetation reconstructions and physical geochemical datasets are presented from a peatland in northeastern China. Using 108 modern topsoil samples as a training set, canopy cover and vegetation composition are estimated for the period since 5100 cal. yr BP. Variation partitioning analysis (VPA) is used to determine the relative importance of climate change, human impacts, and paleofire disturbance. The generalized dynamic vegetation model LPJ-GUESS is forced with climate anomaly output from an atmospheric general circulation model to simulate vegetation dynamics during the mid-Holocene and the pre-industrial era. The proxy-based estimates are compared to modelling output. Results indicate that regional tree cover varied from 10% to 40% during the past five millennia. The single-core, phytolith-based reconstructions are generally consistent with stacked tree pollen z-scores calculated from different records along the East Asian monsoon margin, implying that mid-Holocene tree cover decrease was persistent and almost synchronous over extensive areas. VPA demonstrates that long-term monsoon marginal vegetation successions were mainly caused by climate effects. Numerical modelling suggests that since the mid-Holocene the retreat of forests along the monsoon margin was primarily associated with precipitation deficits. Our investigation highlights that the precipitation associated with the East Asian monsoon system has exerted a stronger influence than the westerlies on the monsoon margin climate and vegetation change. With ongoing global change, close attention to variations in precipitation patterns and amounts should be especially helpful in efforts aimed at ecological monitoring, change prediction, and restoration.
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| 2. |
- Li, Xixing, et al.
(author)
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Flexible Job Shop Composite Dispatching Rule Mining Approach Based on an Improved Genetic Programming Algorithm
- 2024
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In: Tsinghua Science and Technology. - : Tsinghua University. - 1007-0214 .- 1878-7606. ; 29:5, s. 1390-1408
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Journal article (peer-reviewed)abstract
- To obtain a suitable scheduling scheme in an effective time range, the minimum completion time is taken as the objective of Flexible Job Shop scheduling Problems (FJSP) with different scales, and Composite Dispatching Rules (CDRs) are applied to generate feasible solutions. Firstly, the binary tree coding method is adopted, and the constructed function set is normalized. Secondly, a CDR mining approach based on an Improved Genetic Programming Algorithm (IGPA) is designed. Two population initialization methods are introduced to enrich the initial population, and a superior and inferior population separation strategy is designed to improve the global search ability of the algorithm. At the same time, two individual mutation methods are introduced to improve the algorithm’s local search ability, to achieve the balance between global search and local search. In addition, the effectiveness of the IGPA and the superiority of CDRs are verified through comparative analysis. Finally, Deep Reinforcement Learning (DRL) is employed to solve the FJSP by incorporating the CDRs as the action set, the selection times are counted to further verify the superiority of CDRs.
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| 3. |
- Kim, Woonghee, et al.
(author)
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Characterization of an in vitro steatosis model simulating activated de novo lipogenesis in MAFLD patients
- 2023
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In: iScience. - : Elsevier BV. - 2589-0042. ; 26:10
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Journal article (peer-reviewed)abstract
- Activated de novo lipogenesis (DNL) is the critical pathway involved in the progression of metabolic-associated fatty liver disease (MAFLD). We present an in vitro steatosis model for MAFLD that induces steatosis through activated DNL. This model utilizes insulin and LXR receptor ligand T0901317, eliminating the need for fatty acid treatment. Significant increases in triglycerides (TAGs) and expression of DNL-related transcription factors were observed. Transcriptomic analysis revealed distinct gene expression profiles between the DNL and conventional oleic acid (OA)-induced steatosis model. DNL steatosis model exhibited elevated pathways related to glycolysis, cholesterol homeostasis, and bile acid metabolism, reflecting its clinical relevance to MAFLD. Moreover, C75 and JNK-IN-5A compounds effectively reduced TAG accumulation and steatosis-related protein expression in the DNL model, whereas they had no significant impact on TAG accumulation in the OA model. In conclusion, we introduce an ideal model for steatosis study, which could help in understanding the MAFLD mechanisms.
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| 4. |
- Yang, Hong, et al.
(author)
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Integrative proteo-transcriptomic characterization of advanced fibrosis in chronic liver disease across etiologies
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Other publication (other academic/artistic)abstract
- Various causes of chronic hepatic injury and inflammation can lead to fibrosis and cirrhosis, potentially predisposing individuals to hepatocellular carcinoma. Despite extensive research, the molecular mechanisms underlying liver fibrosis and its associated progression to cancer remain incompletely understood. In this study, we employed an integrated proteotranscriptomics approach to characterize the molecular pathophysiology of liver fibrosis in both liver and plasma samples from 330 individuals. This cohort included 40 healthy subjects and 290 patients with histologically characterized fibrosis due to chronic viral infection, alcohol consumption, or metabolic-dysfunction associated steatotic liver disease. We demonstrated that pathways related to extracellular matrix alterations, immune response, inflammation, and metabolism are dysregulated in advanced hepatic fibrosis, regardless of the underlying cause. Additionally, our analysis of peritumoral hepatic tissues revealed transcription signatures linked to cell proliferation, survival, and inflammation in hepatocellular carcinoma. Furthermore, we observed extensive remodeling of the plasma proteome linked with severe fibrosis and identified 132 circulating proteomic signatures associated with advanced fibrosis by integrative analysis of plasma proteomics with hepatic transcriptomics. We finally developed predictive models using machine learning to facilitate the non-invasive detection of advanced fibrosis and cirrhosis.
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