Xiangcheng Xiao

Dr. Xiangcheng Xiao

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 April 2020 in European Journal of Clinical Microbiology & Infectious Diseases
Verified
Journal Article
Open access
PDF file
HGHuipeng Ge
Huipeng Ge
XWXiufen Wang
Xiufen Wang
XYXiangning Yuan
Xiangning Yuan
GXGong Xiao
Gong Xiao
CWChengzhi Wang
Chengzhi Wang
XXXiangcheng Xiao
Xiangcheng Xiao
In December 2019, pneumonia of unknown cause occurred in Wuhan, Hubei Province, China. On 7 January 2020, a novel coronavirus, named as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was identified in the throat swab sample of one patient. The World Health Organization (WHO) announced the epidemic disease caused by SARS-CoV-2 as coronavirus disease 2019 (COVID-19). Currently, COVID-19 has spread widely around the world, affecting more than seventy countries. China, with a huge burden of this disease, has taken strong measures to control the spread and improve the curative rate of COVID-19. In this review, we summarized the epidemiological characteristics, clinical features, diagnosis, treatment, and prognosis of COVID-19. A comprehensive understanding will help to control the disease.

16 April 2021 in Frontiers in Immunology
Verified
Journal Article
Open access
RTRong Tang
Rong Tang
TMTing Meng
Ting Meng
WLWei Lin
Wei Lin
CSChanjuan Shen
Chanjuan Shen
JOJoshua D. Ooi
Joshua D. Ooi
XXXiangcheng Xiao
Xiangcheng Xiao
The molecular mechanisms underlying renal damage of IgA nephropathy (IgAN) remain incompletely defined. Here, single-cell RNA sequencing (scRNA-seq) was applied to kidney biopsies from IgAN and control subjects to define the transcriptomic landscape at single-cell resolution. We presented a comprehensive scRNA-seq analysis of human renal biopsies from IgAN. We showed for the first time that IgAN mesangial cells displayed increased expression of several novel genes including MALAT1, GADD45B, SOX4, and EDIL3, which were related to cell proliferation and matrix accumulation. The overexpressed genes in tubule cells of IgAN were mainly enriched in inflammatory pathways including TNF signaling, IL-17 signaling, and NOD-like receptor signaling. Furthermore, we compared the results of 4 IgAN patients with the published scRNA-Seq data of healthy kidney tissues of three human donors in order to further validate the findings in our study. The results also verified that the overexpressed genes in tubule cells from IgAN patients were mainly enriched in inflammatory pathways including TNF signaling, IL-17 signaling, and NOD-like receptor signaling. The receptor-ligand crosstalk analysis revealed potential interactions between mesangial cells and other cells in IgAN. IgAN patients with overt proteinuria displayed elevated genes participating in several signaling pathways compared with microproteinuria group. It needs to be mentioned that based on number of mesangial cells and other kidney cells analyzed in this study, the results of our study are preliminary and needs to be confirmed on larger number of cells from larger number of patients and controls in future studies. Therefore, these results offer new insight into pathogenesis and identify new therapeutic targets for IgAN.

15 March 2019 in Journal of Translational Medicine
Verified
Journal Article
Open access
PDF file
QYQiongjing Yuan
Qiongjing Yuan
Jinwei WangJinwei Wang
Jinwei Wang
ZPZhangzhe Peng Peng
Zhangzhe Peng Peng
QZQiaoling Zhou
Qiaoling Zhou
XXXiangcheng Xiao
Xiangcheng Xiao
CGC-STRIDE study group
C-STRIDE study group
Background: Chronic kidney disease (CKD) leads to end-stage renal failure and cardiovascular events. An attribute to these progressions is abnormalities in inflammation, which can be evaluated using the neutrophil-to-lymphocyte ratio (NLR). We aimed to investigate the association of NLR with the progression of end stage of renal disease (ESRD), cardiovascular disease (CVD) and all-cause mortality in Chinese patients with stages 1–4 CKD. Methods: Patients with stages 1–4 CKD (18–74 years of age) were recruited at 39 centers in 28 cities across 22 provinces in China since 2011. A total of 938 patients with complete NLR and other relevant clinical variables were included in the current analysis. Cox regression analysis was used to estimate the association between NLR and the outcomes including ESRD, CVD events or all-cause mortality. Results: Baseline NLR was related to age, hypertension, serum triglycerides, total serum cholesterol, CVD history, urine albumin to creatinine ratio (ACR), chronic kidney disease-mineral and bone disorder (CKD-MBD), hyperlipidemia rate, diabetes, and estimated glomerular filtration rate (eGFR). The study duration was 4.55 years (IQR 3.52–5.28). Cox regression analysis revealed an association of NLR and the risk of ESRD only in patients with stage 4 CKD. We did not observe any significant associations between abnormal NLR and the risk of either CVD or all-cause mortality in CKD patients in general and CKD patients grouped according to the disease stages in particular. Conclusion: Our results suggest that NLR is associated with the risk of ESRD in Chinese patients with stage 4 CKD. NLR can be used in risk assessment for ESRD among patients with advanced CKD; this application is appealing considering NLR being a routine test. Trial registration ClinicalTrials.gov Identifier NCT03041987. Registered January 1, 2012. (retrospectively registered) (https://www.clinicaltrials.gov/ct2/show/NCT03041987?term=Chinese+Cohort+Study+of+Chronic+Kidney+Disease+%28C-STRIDE%29&rank=1)

1 January 2020 in International Journal of Medical Sciences
Verified
Journal Article
Open access
QYQiongjing Yuan
Qiongjing Yuan
HZHaixia Zhang
Haixia Zhang
TDTianci Deng
Tianci Deng
STShumei Tang
Shumei Tang
XYXiangning Yuan
Xiangning Yuan
XXXiangcheng Xiao
Xiangcheng Xiao
Artificial intelligence (AI), as an advanced science technology, has been widely used in medical fields to promote medical development, mainly applied to early detections, disease diagnoses, and management. Owing to the huge number of patients, kidney disease remains a global health problem. Challenges remain in its diagnosis and treatment. AI could take individual conditions into account, produce suitable decisions and promise to make great strides in kidney disease management. Here, we review the current studies of AI applications in kidney disease in alerting systems, diagnostic assistance, guiding treatment and evaluating prognosis. Although the number of studies related to AI applications in kidney disease is small, the potential of AI in the management of kidney disease is well recognized by clinicians; AI will greatly enhance clinicians' capacity in their clinical practice in the future.

25 November 2019 in International Urology and Nephrology
Verified
Journal Article
Closed access
PDF file
STShumei Tang
Shumei Tang
XXXiangcheng Xiao
Xiangcheng Xiao

10 August 2020 in Scientific Reports
Verified
Journal Article
Open access
PDF file
STShuMei Tang
ShuMei Tang
XWXiuFen Wang
XiuFen Wang
TDTianCi Deng
TianCi Deng
HGHuiPeng Ge
HuiPeng Ge
XXXiangcheng Xiao
Xiangcheng Xiao
The pathogenesis of diabetic nephropathy is not completely understood, and the effects of existing treatments are not satisfactory. Various public platforms already contain extensive data for deeper bioinformatics analysis. From the GSE30529 dataset based on diabetic nephropathy tubular samples, we identified 345 genes through differential expression analysis and weighted gene coexpression correlation network analysis. GO annotations mainly included neutrophil activation, regulation of immune effector process, positive regulation of cytokine production and neutrophil-mediated immunity. KEGG pathways mostly included phagosome, complement and coagulation cascades, cell adhesion molecules and the AGE-RAGE signalling pathway in diabetic complications. Additional datasets were analysed to understand the mechanisms of differential gene expression from an epigenetic perspective. Differentially expressed miRNAs were obtained to construct a miRNA-mRNA network from the miRNA profiles in the GSE57674 dataset. The miR-1237-3p/SH2B3, miR-1238-5p/ZNF652 and miR-766-3p/TGFBI axes may be involved in diabetic nephropathy. The methylation levels of the 345 genes were also tested based on the gene methylation profiles of the GSE121820 dataset. The top 20 hub genes in the PPI network were discerned using the CytoHubba tool. Correlation analysis with GFR showed that SYK, CXCL1, LYN, VWF, ANXA1, C3, HLA-E, RHOA, SERPING1, EGF and KNG1 may be involved in diabetic nephropathy. Eight small molecule compounds were identified as potential therapeutic drugs using Connectivity Map.