1.Platelet-rich plasma ameliorates photo-aging phenotype of fibroblasts by adjusting the generation of reactive oxygen species
Chuanlong JIA ; QingJian YANG ; Bo BI ; Tianyi LIU ; Liang CHEN ; Yu GU ; YiQun ZHOU ; Ping YANG ; NingWen ZHU ; JingJing ZHU ; Dengke QING
Chinese Journal of Medical Aesthetics and Cosmetology 2018;24(1):54-57
Objective To explore the effect of platelet-rich plasma (PRP) on the generation of reactive oxygen species (ROS) and the phenotypes of photo-aging fibroblasts.Methods A photoaging cell model by repeating UVB irradiation was treated using appropriate concentration of PRP;Cell morphology and the rate of aging dying were observed under inverted microscope 24 hours later after establishment of the cell model;The expression of ROS between experimental and control group was detected using fluorescence microscope after single UVB irradiation.The relative intensity of fluorescence was analyzed using flow cytometry.Results PRP could ameliorate the large and sprawl appearance of photoaging fibroblasts obviously,reduce the generation of ROS as well as decrease the relative intensity of ROS.Conclusions PRP can decrease the level of intracellular oxidative stress caused by UVB irradiation,reduce the generation of ROS and ameliorate the senescence-like phenotypes of pho toaging fibroblasts.
2.Diagnostic value of a combined serology-based model for minimal hepatic encephalopathy in patients with compensated cirrhosis
Shanghao LIU ; Hongmei ZU ; Yan HUANG ; Xiaoqing GUO ; Huiling XIANG ; Tong DANG ; Xiaoyan LI ; Zhaolan YAN ; Yajing LI ; Fei LIU ; Jia SUN ; Ruixin SONG ; Junqing YAN ; Qing YE ; Jing WANG ; Xianmei MENG ; Haiying WANG ; Zhenyu JIANG ; Lei HUANG ; Fanping MENG ; Guo ZHANG ; Wenjuan WANG ; Shaoqi YANG ; Shengjuan HU ; Jigang RUAN ; Chuang LEI ; Qinghai WANG ; Hongling TIAN ; Qi ZHENG ; Yiling LI ; Ningning WANG ; Huipeng CUI ; Yanmeng WANG ; Zhangshu QU ; Min YUAN ; Yijun LIU ; Ying CHEN ; Yuxiang XIA ; Yayuan LIU ; Ying LIU ; Suxuan QU ; Hong TAO ; Ruichun SHI ; Xiaoting YANG ; Dan JIN ; Dan SU ; Yongfeng YANG ; Wei YE ; Na LIU ; Rongyu TANG ; Quan ZHANG ; Qin LIU ; Gaoliang ZOU ; Ziyue LI ; Caiyan ZHAO ; Qian ZHAO ; Qingge ZHANG ; Huafang GAO ; Tao MENG ; Jie LI ; Weihua WU ; Jian WANG ; Chuanlong YANG ; Hui LYU ; Chuan LIU ; Fusheng WANG ; Junliang FU ; Xiaolong QI
Chinese Journal of Laboratory Medicine 2023;46(1):52-61
Objective:To investigate the diagnostic accuracy of serological indicators and evaluate the diagnostic value of a new established combined serological model on identifying the minimal hepatic encephalopathy (MHE) in patients with compensated cirrhosis.Methods:This prospective multicenter study enrolled 263 compensated cirrhotic patients from 23 hospitals in 15 provinces, autonomous regions and municipalities of China between October 2021 and August 2022. Clinical data and laboratory test results were collected, and the model for end-stage liver disease (MELD) score was calculated. Ammonia level was corrected to the upper limit of normal (AMM-ULN) by the baseline blood ammonia measurements/upper limit of the normal reference value. MHE was diagnosed by combined abnormal number connection test-A and abnormal digit symbol test as suggested by Guidelines on the management of hepatic encephalopathy in cirrhosis. The patients were randomly divided (7∶3) into training set ( n=185) and validation set ( n=78) based on caret package of R language. Logistic regression was used to establish a combined model of MHE diagnosis. The diagnostic performance was evaluated by the area under the curve (AUC) of receiver operating characteristic curve, Hosmer-Lemeshow test and calibration curve. The internal verification was carried out by the Bootstrap method ( n=200). AUC comparisons were achieved using the Delong test. Results:In the training set, prevalence of MHE was 37.8% (70/185). There were statistically significant differences in AMM-ULN, albumin, platelet, alkaline phosphatase, international normalized ratio, MELD score and education between non-MHE group and MHE group (all P<0.05). Multivariate Logistic regression analysis showed that AMM-ULN [odds ratio ( OR)=1.78, 95% confidence interval ( CI) 1.05-3.14, P=0.038] and MELD score ( OR=1.11, 95% CI 1.04-1.20, P=0.002) were independent risk factors for MHE, and the AUC for predicting MHE were 0.663, 0.625, respectively. Compared with the use of blood AMM-ULN and MELD score alone, the AUC of the combined model of AMM-ULN, MELD score and education exhibited better predictive performance in determining the presence of MHE was 0.755, the specificity and sensitivity was 85.2% and 55.7%, respectively. Hosmer-Lemeshow test and calibration curve showed that the model had good calibration ( P=0.733). The AUC for internal validation of the combined model for diagnosing MHE was 0.752. In the validation set, the AUC of the combined model for diagnosing MHE was 0.794, and Hosmer-Lemeshow test showed good calibration ( P=0.841). Conclusion:Use of the combined model including AMM-ULN, MELD score and education could improve the predictive efficiency of MHE among patients with compensated cirrhosis.