Browsing by Author "Wang, Liping"

Now showing 1 - 3 of 3
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    Cardiolipin deficiency disrupts CoQ redox state and induces steatohepatitis
    (bioRxiv, 2024-10-10) Brothwell, Marisa J.; Cao, Guoshen; Maschek, J. Alan; Poss, Annelise M.; Peterlin, Alek D.; Wang, Liping; Baker, Talia B.; Shahtout, Justin L.; Siripoksup, Piyarat; Pearce, Quentinn J.; Johnson, Jordan M.; Finger, Fabian M.; Prola, Alexandre; Pellizzari, Sarah A.; Hale, Gillian L.; Manuel, Allison M.; Watanabe, Shinya; Miranda, Edwin R.; Affolter, Kajsa E.; Tippetts, Trevor S.; Nikolova, Linda S.; Choi, Ran Hee; Decker, Stephen T.; Patil, Mallikarjun; Catrow, J. Leon; Holland, William L.; Nowinski, Sara M.; Lark, Daniel S.; Fisher-Wellman, Kelsey H.; Mimche, Patrice N.; Evason, Kimberley J.; Cox, James E.; Summers, Scott A.; Gerhart-Hines, Zach; Funai, Katsuhiko; Dermatology, School of Medicine
    Metabolic dysfunction-associated steatotic liver disease (MASLD) is a progressive disorder marked by lipid accumulation, leading to steatohepatitis (MASH). A key feature of the transition to MASH involves oxidative stress resulting from defects in mitochondrial oxidative phosphorylation (OXPHOS). Here, we show that pathological alterations in the lipid composition of the inner mitochondrial membrane (IMM) directly instigate electron transfer inefficiency to promote oxidative stress. Specifically, cardiolipin (CL) was downregulated across four mouse models of MASLD. Hepatocyte-specific CL synthase knockout (CLS-LKO) led to spontaneous MASH with elevated mitochondrial electron leak. Loss of CL interfered with the ability of coenzyme Q (CoQ) to transfer electrons, promoting leak primarily at sites IIF and IIIQ0. Data from human liver biopsies revealed a highly robust correlation between mitochondrial CL and CoQ, co-downregulated with MASH. Thus, reduction in mitochondrial CL promotes oxidative stress and contributes to pathogenesis of MASH.
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    Multi-omic profiling of clear cell renal cell carcinoma identifies metabolic reprogramming associated with disease progression
    (Springer Nature, 2024) Hu, Junyi; Wang, Shao-Gang; Hou, Yaxin; Chen, Zhaohui; Liu, Lilong; Li, Ruizhi; Li, Nisha; Zhou, Lijie; Yang, Yu; Wang, Liping; Wang, Liang; Yang, Xiong; Lei, Yichen; Deng, Changqi; Li, Yang; Deng, Zhiyao; Ding, Yuhong; Kuang, Yingchun; Yao, Zhipeng; Xun, Yang; Li, Fan; Li, Heng; Hu, Jia; Liu, Zheng; Wang, Tao; Hao, Yi; Jiao, Xuanmao; Guan, Wei; Tao, Zhen; Ren, Shancheng; Chen, Ke; Pathology and Laboratory Medicine, School of Medicine
    Clear cell renal cell carcinoma (ccRCC) is a complex disease with remarkable immune and metabolic heterogeneity. Here we perform genomic, transcriptomic, proteomic, metabolomic and spatial transcriptomic and metabolomic analyses on 100 patients with ccRCC from the Tongji Hospital RCC (TJ-RCC) cohort. Our analysis identifies four ccRCC subtypes including De-clear cell differentiated (DCCD)-ccRCC, a subtype with distinctive metabolic features. DCCD cancer cells are characterized by fewer lipid droplets, reduced metabolic activity, enhanced nutrient uptake capability and a high proliferation rate, leading to poor prognosis. Using single-cell and spatial trajectory analysis, we demonstrate that DCCD is a common mode of ccRCC progression. Even among stage I patients, DCCD is associated with worse outcomes and higher recurrence rate, suggesting that it cannot be cured by nephrectomy alone. Our study also suggests a treatment strategy based on subtype-specific immune cell infiltration that could guide the clinical management of ccRCC.
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    Prediction of soil organic matter using VNIR spectral parameters extracted from shape characteristics
    (Elsevier, 2022-02) Wang, Xiang; Li, Lin; Liu, Huanjun; Song, Kaishan; Wang, Liping; Meng, Xiangtian; Earth Science, School of Science
    Whether spectral feature parameters (SFPs) can be effectively used to predict soil organic matter (SOM), and its spatial transferability was tested for different regions. In this study, a hybrid model was proposed based on SFPs and local regression method. The topsoil spectra of 221 soil samples from Sanjiang Plain and 187 soil samples from Nong’an county in Northeast China were re-sampled (at 0.01 µm intervals) and converted to the first-derivative curves and CR curves. Two SFPs were extracted on reflectance curves (RSFPs), which were defined as curve length (Lc) and area (Ac) between two absorption positions. Local random forest models with k-means clustering were built using the RSFPs and first-derivative spectra for evaluating the feasibility of RSFPs in these two study areas. After analyzing the results of Chinese soil samples, this method was also applied to Land Use/Land Cover Area Frame Survey (LUCAS) topsoil database in order to evaluate the feasibility of RSFPs outside China. Our results revealed these: (1) high correlation between the RSFPs of soil samples with spectral characteristics of sandy soils and SOM; (2) the importance of Lc relative to Ac in SOM prediction is higher; and (3) SOM prediction using RSFPs is comparable to the first-derivative spectra, and the best result has an R2 of 0.76 and an RMSE of 7.43 g kg−1. Our results suggest that RSFPs can be used to predict SOM and have good spatial transferability after applying in two study areas. RSFPs with specific geometric meaning have high potential to predict other soil properties in Northeast China. Our results also provide a reference for SOM mapping using hyper-spectral satellites.