Fu Ren

Dr. Fu Ren

orcid

Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

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

Representative Publications

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1 March 2014 in Experimental Gerontology
Verified
Journal Article
Open access
MGMichael Gardner
Michael Gardner
DBDavid Bann
David Bann
LWLaura Wiley
Laura Wiley
RCRachel Cooper
Rachel Cooper
RHRebecca Hardy
Rebecca Hardy
YBYoav Ben-Shlomo
Yoav Ben-Shlomo
It is widely believed that females have longer telomeres than males, although results from studies have been contradictory. We carried out a systematic review and meta-analyses to test the hypothesis that in humans, females have longer telomeres than males and that this association becomes stronger with increasing age. Searches were conducted in EMBASE and MEDLINE (by November 2009) and additional datasets were obtained from study investigators. Eligible observational studies measured telomeres for both females and males of any age, had a minimum sample size of 100 and included participants not part of a diseased group. We calculated summary estimates using random-effects meta-analyses. Heterogeneity between studies was investigated using sub-group analysis and meta-regression. Meta-analyses from 36 cohorts (36,230 participants) showed that on average females had longer telomeres than males (standardised difference in telomere length between females and males 0.090, 95% CI 0.015, 0.166; age-adjusted). There was little evidence that these associations varied by age group (p=1.00) or cell type (p=0.29). However, the size of this difference did vary by measurement methods, with only Southern blot but neither real-time PCR nor Flow-FISH showing a significant difference. This difference was not associated with random measurement error. Telomere length is longer in females than males, although this difference was not universally found in studies that did not use Southern blot methods. Further research on explanations for the methodological differences is required.

23 August 2022 in Redox Biology
Verified
Journal Article
Open access
LLLihua Li
Lihua Li
KWKunpeng Wang
Kunpeng Wang
RJRongjun Jia
Rongjun Jia
JXJing Xie
Jing Xie
LMLiman Ma
Liman Ma
FRFu Ren
Fu Ren
Chronic liver injury causing liver fibrosis is a major cause of morbidity and mortality worldwide. Targeting the suppression of hepatic stellate cell (HSC) activation is recognized as an effective strategy for the treatment of liver fibrosis. Ellagic acid (EA), a natural polyphenol product isolated from fruits and vegetables, possesses many biological functions. Here, EA exerts its antifibrotic activity by inducing ferroptotic cell death of activated HSCs, which is accompanied by redox-active iron accumulation, lipid peroxidation, and GSH depletion in CCl4 mice and human LX-2 cells. The specific ferroptosis inhibitor ferrostatin-1 prevented EA-induced ferroptotic cell death. Mechanistically, EA impairs the formation of vesicle-associated membrane protein 2 (VAMP2)/syntaxin 4 and VAMP2/synaptosome-associated protein 23 complexes by suppressing VAMP2 expression by enhancing its degradation in a proteasome-dependent pathway. This leads to the impairment of ferroportin (FPN, an iron exporter) translocation and intracellular iron extrusion. Interestingly, VAMP2 overexpression inhibits the role of EA in blocking FPN translocation and increasing intracellular ferritin content (an iron storage marker). In contrast, VAMP2 knockdown shows a synergistic effect on EA-mediated ferroptotic events in both HSCs. Additionally, HSC-specific overexpression of VAMP2 impaired EA-induced HSC ferroptosis in mouse liver fibrosis, and HSC-specific VAMP2 knockdown increased the inhibitory effect of EA on fibrosis. Taken together, our data suggest that the natural product EA exerts its antifibrotic effects by inducing FPN-dependent ferroptosis of HSCs by disrupting the formation of SNARE complexes, and EA will hopefully serve as a prospective compound for liver fibrosis treatment.

1 May 2020 in Experimental Cell Research
Verified
Journal Article
Closed access
SPShuang Pan
Shuang Pan
FRFu Ren
Fu Ren
LLLei Li
Lei Li
DLDahua Liu
Dahua Liu
YLYao Li
Yao Li
WGWenjuan Guo
Wenjuan Guo

1 September 2009 in American Journal of Forensic Medicine & Pathology
Verified
Journal Article
Closed access
FRFu Ren
Fu Ren
CLChangyong Li
Changyong Li
HXHuanjiu Msc Xi
Huanjiu Msc Xi
YWYoufeng Wen
Youfeng Wen
KHKeqiang Msc Huang
Keqiang Msc Huang
In most normal somatic cells, the terminal restriction fragments (TRF) length and age are inversely correlated, which can be used to determine individual age. However, very little is known about the quantitative relationship between human telomeres and age. The aim of the present study was to investigate age-, gender-, and ethnicity-related changes in telomere length in human peripheral blood leukocytes (PBLs). Changes with age in telomere lengths were assessed by Southern blotting. The results shown that telomeres shorten in human PBLs in an age-dependent manner (r = −0.913, P < 0.01). The formula for age estimation according to telomere shortening was Y = −16.539X + 236.287 (Y: age, year; X: mean TRF length, kb). We analyzed the mean TRF length in males and females and found that males had shorter telomeres than females. Moreover, we compared the TRF length of Tibetan and Han population in China and found that telomere length did not differ between 2 populations. We conclude that estimation of human age according to telomere shortening in PBLs is a novel method especially when there is no morphologic information, furthermore, the gender must be considered when age estimation is carried out based on telomere shortening.

3 April 2013 in Aging Clinical and Experimental Research
Verified
Journal Article
Closed access
PDF file
HXHuanjiu Xi
Huanjiu Xi
CLChangyong Li
Changyong Li
FRFu Ren
Fu Ren
HZHailong Zhang
Hailong Zhang
LZLuping Zhang
Luping Zhang

1 June 2024 in European Journal of Pharmacology
Verified
Journal Article
Closed access
YZYaoxia Zhang
Yaoxia Zhang
YQYuanyuan Qu
Yuanyuan Qu
RCRuiping Cai
Ruiping Cai
JGJunjia Gao
Junjia Gao
QXQian Xu
Qian Xu
MZMing-Sheng Zhou
Ming-Sheng Zhou