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13. Relationship of serum total cholesterol and triglyceride with risk of mortality in maintenance hemodialysis patients: a multicenter prospective cohort study

Author

Huang, Yan, primary, Zhong, Qiuxia, additional, Chen, Junzhi, additional, Qin, Xianhui, additional, Yang, Yaya, additional, He, Yanhuan, additional, Lin, Zizhen, additional, Li, Yumin, additional, Yang, Shenglin, additional, Lu, Yongxin, additional, Zhao, Yanhong, additional, Kong, Yaozhong, additional, Wan, Qijun, additional, Wang, Qi, additional, Huang, Sheng, additional, Liu, Yan, additional, Liu, Aiqun, additional, Liu, Fanna, additional, Hou, Fanfan, additional, and Liang, Min, additional

Published
2024
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28. Correlation of Serum FGF23 and Chronic Kidney Disease-Mineral and Bone Abnormality Markers With Cardiac Structure Changes in Maintenance Hemodialysis Patients

Author

Zeng, Dewang, primary, Zha, Aiyun, additional, Lei, Ying, additional, Yu, Zongchao, additional, Cao, Rui, additional, Li, Ling, additional, Song, Zhuoheng, additional, Li, Weilong, additional, Li, Yunyi, additional, Liu, Haiping, additional, Huang, Shaoxing, additional, Dong, Xiangnan, additional, Krämer, Bernhard, additional, Hocher, Berthold, additional, Yin, Lianghong, additional, Yun, Chen, additional, Morgera, Stanislao, additional, Guan, Baozhang, additional, Meng, Yu, additional, Liu, Fanna, additional, Hu, Bo, additional, and Luan, Shaodong, additional

Published
2023
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35. Low BMI and high waist-to-hip ratio are associated with mortality risk among hemodialysis patients: a multicenter prospective cohort study

Author

Yang, Yaya, primary, Zhang, Haixia, additional, Lan, Xiaolei, additional, Qin, Xianhui, additional, Huang, Yan, additional, Wang, Jieyu, additional, Luo, Pei, additional, Wen, Zhen, additional, Li, Yumin, additional, Kong, Yaozhong, additional, Wan, Qijun, additional, Wang, Qi, additional, Huang, Sheng, additional, Liu, Yan, additional, Liu, Aiqun, additional, Liu, Fanna, additional, Yang, Shenglin, additional, Lu, Yongxin, additional, Zhao, Yanhong, additional, Chen, Junzhi, additional, Lei, Zihan, additional, He, Yanhuan, additional, Lin, Zizhen, additional, Li, Youbao, additional, and Liang, Min, additional

Published
2022
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40. Additional file 1 of Integrating spatial transcriptomics with single-cell transcriptomics reveals a spatiotemporal gene landscape of the human developing kidney

Author

Wu, Hongwei, Liu, Fanna, Shangguan, Yu, Yang, Yane, Shi, Wei, Hu, Wenlong, Zeng, Zhipeng, Hu, Nan, Zhang, Xinzhou, Hocher, Berthold, Tang, Donge, Yin, Lianghong, and Dai, Yong

Abstract

Additional file 1: Figure S1. scRNA-seq analysis of two human embryonic kidneys from 9 and 18 post-conception weeks. (a) Schematic of the experimental design and analysis. (b) Distribution of the number of transcripts and genes detected per spot at 9 and 18 PCW kidneys. Blue dashed lines indicate mean values, while the red dashed lines indicate the standard deviation. (c) Dimensionality reduction and clustering of the scRNA-seq data of the 9 and 18 PCW kidneys based on UMAP. (d) Quality control of the scRNA-seq data. ScRNA-seq dataset of fetal kidneys at 9 and 18 weeks post-conception are downloaded online (accession number: GSE114530). (e) Annotation of the cell types identified by spatial transcriptomics data based on the specific cell-type marker genes known from the literature. ST-seq, spatial transcriptomics sequencing; scRNA-seq, single-cell RNA sequencing; PCW, post-conception weeks; ICs, interstitial cells; PTA, pretubular aggregate; UBCD, ureteric bud/collecting duct; SSBmd/DTLH, distal tubule/loop of Henle and s-shaped body medial precursor cell; NPC, nephron progenitor cell; SSBpr, s-shaped body proximal precursor cell; ErprT, early proximal tubule. PETE, Pelvic segment transitional epithelium; Mes, mesangial cell; Pod, podocyte. Figure S2. Cell-type deconvolution of the kidney tissues from 9 and 18 weeks post-conception. (a) Spatial location and clustering of ST-seq spots. (b) The proportion of signatures of different scRNA-seq cell types in each ST spot of the 18 PCW kidney tissue. Each pie chart represents the contribution of scRNA-seq cell types to the transcriptomic signature of each ST spot. Only cell types that contribute at least 10% to the spot signature are shown. (c) Up: multimodal intersection analysis (MIA) of scRNA-seq-identified cell types and ST-defined clusters. * represents the closest relationship between scRNA-identified cell types and the ST-defined clusters (P < 0.01). Down: the spatial mapping of scRNA-seq cell subsets performed by MIA. (d) The proportion of each scRNA-seq cell subpopulation arising from each ST spot in the 9 and 18 PCW kidneys. (e) Fraction of total signature of each cell type present in the cortex, medulla, and pelvis in the 18 PCW kidney. (f) Fraction of total signature of each cell type present in the cortex, medulla, and pelvis in the adult human kidney (Ricardo et al.). Figure S3. Energy metabolism features of the renal cortex and medulla. Heatmaps displaying the expression levels of (a) OXPHOS-related genes and (b) glycolysis-related genes in scRNA-identified cell types in Hochane’s study. (c) G2/M scores and mean expression levels of proliferation markers (Z-scores) per scRNA-identified cell subpopulation. This image is from Hochane’s study. (d) The distribution feature of the dominated cell types in the cortical region of the 18 PCW kidney. (e) The distribution feature of the dominated cell types in the medullary region of the 18 PCW kidney. Figure S4. The biological function of the 16 distinct co-expressed patterns obtained from weighted gene co-expression network analysis. Left, diagrammatic drawing showing the relevance between the 16 modules and corresponding biological function. Scale bar: red represents a strong correlation, and gray indicates that the change in biological function did not reach the P-value threshold. Right, identification of biological function based on the differentially expressed genes in each module. Figure S5. Expression levels of M5 network genes for each (a) ST-seq and (b) scRNA-seq cell subpopulation. Figure S6. The expression of ribosome-related genes in NPC and PTA clusters identified in Hochane’s study. The structure chart on the top left corner shows the spatial location of the NPC and PTA clusters. Violin plots showing the expression of ribosome-related genes in NPC and PTA clusters. Figure S7. Development of the nephric duct. (a) Schematic diagram showing the outgrowth of the UB and its regulatory network. UMPA showing the expression of regulatory genes controlling UB development in the 15 spatial cell clusters. (b) Matching plots show the significant signaling transduction regulation between NPC, PTA, and UB cells (score >0.5 and a P

Published
2022
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41. Low BMI and high waist-to-hip ratio are associated with mortality risk among hemodialysis patients: a multicenter prospective cohort study.

Author

Yang, Yaya, Zhang, Haixia, Lan, Xiaolei, Qin, Xianhui, Huang, Yan, Wang, Jieyu, Luo, Pei, Wen, Zhen, Li, Yumin, Kong, Yaozhong, Wan, Qijun, Wang, Qi, Huang, Sheng, Liu, Yan, Liu, Aiqun, Liu, Fanna, Yang, Shenglin, Lu, Yongxin, Zhao, Yanhong, and Chen, Junzhi

Subjects
WAIST-hip ratio, HEMODIALYSIS patients, COHORT analysis, PROPORTIONAL hazards models, LONGITUDINAL method
Abstract

Background Data are limited on the relationship between waist-to-hip ratio (WHR) and mortality risk among maintenance hemodialysis (MHD) patients. Moreover, the combined association of body mass index (BMI) and WHR with mortality remains uncertain. Therefore, we aimed to explore the individual and combined association of BMI and WHR with the all-cause and cardiovascular disease (CVD) mortality. Methods In this multicenter prospective cohort study, we enrolled 1034 MHD patients. The primary outcome was all-cause mortality and secondary outcome was CVD mortality. Multivariable Cox proportional hazards models were used to evaluate the individual and combined association of BMI and WHR with the risk of mortality. Results A nonlinear inverse relationship was found between BMI and risk of all-cause mortality (P for nonlinearity <.05). Being underweight (<18.5 kg/m2) was associated with higher all-cause mortality risk (HR 1.45; 95% CI 1.08–1.94) compared with normal weight (18.5–23.9 kg/m2), while being overweight (24–27.9 kg/m2; HR 0.96; 95% CI 0.70–1.31) and obese (≥28 kg/m2; HR 1.19; 95% CI 0.62–2.26) showed no significant differences. Of note, WHR was independently and positively associated with all-cause mortality (per standard deviation increase, HR 1.13; 95% CI 1.00–1.27). When analyzed jointly, patients with low BMI (<18.5 kg/m2) and high WHR (≥0.95) had the highest risk of all-cause mortality. Similar results were obtained for CVD mortality. Conclusions In patients undergoing hemodialysis from China, low BMI and high WHR were individually and jointly associated with higher risk of mortality. Our results emphasize that BMI and WHR may jointly affect the prognosis of MHD patients. [ABSTRACT FROM AUTHOR]

Published
2023
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46. RETRACTED ARTICLE: The urinary exosomes derived from premature infants attenuate cisplatin-induced acute kidney injury in mice via microRNA-30a-5p/ mitogen-activated protein kinase 8 (MAPK8)

Author

Ma, Mingming, primary, Luo, Qiao, additional, Fan, Lijing, additional, Li, Weilong, additional, Li, Qiang, additional, Meng, Yu, additional, Yun, Chen, additional, Wu, Hongwei, additional, Lu, Yongping, additional, Cui, Shuang, additional, Liu, Fanna, additional, Hu, Bo, additional, Guan, Baozhang, additional, Liu, Huanhuan, additional, Huang, Shengling, additional, Liang, Wenxue, additional, Morgera, Stanislao, additional, Krämer, Bernhard, additional, Luan, Shaodong, additional, Yin, Lianghong, additional, and Hocher, Berthold, additional

Published
2022
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47. Dietary Plant Protein and Mortality Among Patients Receiving Maintenance Hemodialysis: A Cohort Study

Author

He, Yanhuan, primary, Lu, Yongxin, additional, Yang, Shenglin, additional, Li, Yumin, additional, Yang, Yaya, additional, Chen, Junzhi, additional, Huang, Yan, additional, Lin, Zizhen, additional, Li, Youbao, additional, Kong, Yaozhong, additional, Zhao, Yanhong, additional, Wan, Qijun, additional, Wang, Qi, additional, Huang, Sheng, additional, Liu, Yan, additional, Liu, Aiqun, additional, Liu, Fanna, additional, Hou, Fan Fan, additional, Qin, Xianhui, additional, and Liang, Min, additional

Published
2021
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49. The exosomes derived from urine of premature infants target MAPK8 via miR-30a-5p to protect cisplatin-induced acute kidney injury in mice

Author

Ma, Mingming, primary, Luo, Qiao, additional, Fan, Lijing, additional, Li, Weilong, additional, Li, Qiang, additional, Meng, Yu, additional, Yun, Chen, additional, Wu, Hongwei, additional, Lu, Yongping, additional, Cui, Shuang, additional, Liu, Fanna, additional, Hu, Bo, additional, Guan, Baozhang, additional, Liu, Huanhuan, additional, Huang, Shengling, additional, Liang, Wenxue, additional, Morgera, Stanislao, additional, kraemer, Bernard, additional, Luan, Shaodong, additional, Yin, Lianghong, additional, and Hocher, Berthold, additional

Published
2021
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