Search

Longyi Zheng,1,* Chengjing Zhang,2,* Shichang Bu,1,* Wencheng Guo,3,* Tongtong Li,4 Ying Xu,5 Yunan Liu,4 Caimei Yuan,4 Chengwu Feng,4 Geng Zong,4 Jingwen Zhu,4 Maoying Xing,5 Xin Geng5 1Department of Endocrinology, Changhai Hospital, Naval Medical University, Shanghai, People’s Republic of China; 2Department of Nutrition, Shanghai Eastern Hepatobiliary Surgery Hospital, Shanghai, People’s Republic of China; 3Department of General Surgery and Vascular Surgery, Huashan Hospital, Fudan University, Shanghai, People’s Republic of China; 4CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, People’s Republic of China; 5National Center for Liver Cancer, Naval Medical University, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Maoying Xing; Xin Geng, Email xmyxing@sina.com; gxouc@hotmail.comBackground: Neuregulin 4 (NRG4) was known to be associated with serum lipid levels and atherosclerosis. However, it is unknown whether the role of NRG4 in lipid homeostasis is causal to atherosclerosis and whether the effect is beneficial across different atherosclerosis subtypes.Methods: We investigated the causal role of the levels of serum low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides regulated by NRG4 in subtypes of atherosclerosis through two sample Mendelian randomization. Aggregated genome-wide association study (GWAS) summary data for serum lipid level of 1.32 million individuals with European ancestry were obtained from the Global Lipids Genetics Consortium. GWAS summary data for four atherosclerosis subtypes (peripheral, coronary, cerebral and the other atherosclerosis) were obtained from FinnGen Consortium. Generalized inverse-variance–weighted Mendelian randomization and several sensitivity analyses were used to obtain the causal estimates.Results: A 1-SD genetically elevated LDL-C level mediated by NRG4 was validated to be nominally associated with the risk of peripheral atherosclerosis (log (odds ratio)= 4.14, 95% confidence interval 0.11 to 8.17, P = 0.04), and the other associations were not significant or could not be validated by sensitivity analyses.Conclusion: LDL-C lowering mediated by NRG4 is likely to prevent peripheral atherosclerosis.Keywords: Mendelian randomization analysis, NRG4, atherosclerosis, lipid

Wei Wang,&ast; Fei Teng,&ast; Shi Bu, Wei Xu, Qing-Chun Cai, Yue-Quan Jiang, Zhi-Qiang Wang Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital, Chongqing, 400030, China&ast;These authors contributed equally to this workCorrespondence: Yue-Quan Jiang; Zhi-Qiang Wang, Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital, No. 181 of Hanyu Road, Shapingba District, Chongqing, 400030, China, Tel +86 13708335256 ; +86 15215023098, Email jiangyuequanjyq1@126.com; wangzhiqiangwzq9@126.comObjective: This study aimed to design a nomogram survival prediction by means of the figures retrieved from the Surveillance, Epidemiology, and End Results (SEER) source bank, and to predict the overall survival (OS) of patients with stage IIA non-small cell lung cancer (NSCLC) after surgery.Methods: Data for 4511 patients who had been diagnosed with postoperative stage IIA NSCLC were collected from the SEER databank, while information on 528 patients was acquired from the Chongqing University Cancer Hospital for the external validation cohort. The independent risk factors that affected the prognosis were identified using a multivariate Cox proportional hazards regression model (also used to conduct a nomogram). A survival analysis between the low- and the high-risk groups was performed using the Kaplan–Meier method. Furthermore, a subgroup analysis was conducted of the two groups using the Kaplan–Meier method to determine whether the patients had received adjuvant chemotherapy.Results: The following five variables were integrated into the nomogram: sex (female: HR 1.73, 95% CI 0.64– 0.83), age (≥ 60: HR 1.61, 95% CI 1.39– 1.87), differentiation grade (grade II: HR 2.19, 95% CI 1.66– 2.88; grade III: HR 2.65, 95% CI 2.00– 3.51; grade IV: HR 3.17, 95% CI 1.99– 5.03), surgery (lobectomy: HR 0.72, 95% CI 0.59– 0.86), and lymph node resection (> 12: HR 0.82, 95% CI 0.70– 0.96). Furthermore, the patients selected were categorized into high- and low-risk groups. The OS rate was significantly lower in the high-risk group than in the low-risk group (P < 0.001). Finally, adjuvant chemotherapy was highly correlated with OS in the high-risk set (P = 0.035); however, adjuvant chemotherapy was not related to OS in the low-risk set.Conclusion: A nomogram was created as a reliable, convenient scheme that could predict OS, and it was determined that the high-risk feature patients identified by the nomogram gained benefits from adjuvant chemotherapy.Keywords: nomogram, stage IIA non-small cell lung cancer, adjuvant chemotherapy, OS prediction

Shuqin Chen,1,&ast; Yong Jin,2,&ast; Miao Xu,1 Pingping Zhang,3 Ye Zhou,1 Xingjun Qian,4 Qifa Song,5 Shizhong Bu,6 Jing Sun,7 Li Li1 1Department of Endocrinology and Metabolism, Ningbo First Hospital, Ningbo, Zhejiang Province, People’s Republic of China; 2Department of Internal Medicine, Ningbo Yinzhou Second Hospital, Ningbo, Zhejiang Province, People’s Republic of China; 3School of Public Health, Peking University, Beijing, People’s Republic of China; 4Health Management Center, Ningbo First Hospital, Ningbo, Zhejiang Province, People’s Republic of China; 5Medical Research Center, Ningbo First Hospital, Ningbo, Zhejiang Province, People’s Republic of China; 6Diabetes Research Center, School of Medicine, Ningbo University, Ningbo, Zhejiang Province, People’s Republic of China; 7School of Medicine and Dentistry, Griffith University, Gold Coast, Queensland, Australia&ast;These authors contributed equally to this workCorrespondence: Li Li, Department of Endocrinology and Metabolism, Ningbo First Hospital, Ningbo, Zhejiang Province, People’s Republic of China, Tel +8613757426626, Email lilyningbo@163.com Jing Sun, School of Medicine and Dentistry, Griffith University, Gold Coast, Queensland, Australia, Tel +61756780924, Email j.sun@griffith.edu.auObjective: The thyroid hormone has been demonstrated to be associated with nonalcoholic fatty liver disease (NAFLD) in different populations. However, the relationship between thyroid hormone and the degree of liver steatosis in overweight/obese subjects is still unclear. Liver ultra-sound attenuation (LiSA) is a newly developed ultrasound attenuation parameter for the analysis of hepatic steatosis. The study aimed to characterize the relationship between thyroid hormone and LiSA in overweight/obese participants.Methods: This case-control study was performed in Ningbo First Hospital, China. A total of 24 lean, 66 overweight and 49 obese participants were consecutively recruited from January 2021 to May 2021. Thyroid hormone and other clinical features were measured. LiSA was acquired by using a Hepatus ultrasound machine. Multiple linear regression analyses were performed to examine associations of LiSA and clinic indices.Results: Obese subjects had higher LiSA, fT3 and TSH levels than lean participants of similar age and sex (P < 0.05). LiSA was positively associated with the fT3 level. The multiple linear regression analyses showed that fT3 (ß = 0.353, P < 0.001) was independently associated with LiSA in overweight/obese participants.Conclusion: The fT3 level was independently associated with the degree of liver steatosis among the overweight/obese participants.Keywords: LiSA, obesity, NAFLD, thyroid hormone

Xiaohui Huang,1,* Ze Yu,2,* Shuhong Bu,1 Zhiyan Lin,1 Xin Hao,3 Wenjun He,2 Peng Yu,2 Zeyuan Wang,2 Fei Gao,2 Jian Zhang,1 Jihui Chen1 1Department of Pharmacy, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People’s Republic of China; 2Beijing Medicinovo Technology Co. Ltd., Beijing, People’s Republic of China; 3Dalian Medicinovo Technology Co. Ltd., Dalian, Liaoning Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jihui Chen; Jian ZhangDepartment of Pharmacy, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People’s Republic of ChinaTel +86-2125077155; +86-2125077150Email chenjihui@xinhuamed.com.cn; zhangjian@xinhuamed.com.cnPurpose: This study aimed to establish an optimal model to predict vancomycin trough concentrations by using machine learning.Patients and Methods: We enrolled 407 pediatric patients (age < 18 years) who received vancomycin intravenously and underwent therapeutic drug monitoring from June 2013 to April 2020 at Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine. The median (interquartile range) age and weight of the patients were 2 (0.63– 5) years and 12 (7.8– 19) kg. Vancomycin trough concentrations were considered as the target variable, and eight different algorithms were used for predictive performance comparison. The whole dataset (407 cases) was divided into training group and testing group at the ratio of 80%: 20%, which were 325 and 82 cases, respectively.Results: Ultimately, five algorithms (XGBoost, GBRT, Bagging, ExtraTree and decision tree) with high R 2 (0.657, 0.514, 0.468, 0.425 and 0.450, respectively) were selected and further ensembled to establish the final model and achieve an optimal result. For missing data, through filling the missing values and model ensemble, we obtained R 2=0.614, MAE=3.32, MSE=24.39, RMSE=4.94 and a prediction accuracy of 51.22% (predicted trough concentration within ± 30% of the actual trough concentration). In comparison with the pharmacokinetic models (R 2=0.3), the machine learning model works better in model fitting and has better prediction accuracy.Conclusion: Therefore, the ensemble model is useful for the vancomycin concentration prediction, especially in the population of children with great individual variation. As machine learning methods evolve, the clinical value of the ensemble model will be demonstrated in the clinical practice.Keywords: machine learning, XGBoost, prediction, vancomycin, trough concentration, pediatric patients

Fang Tian,* Jinzhi Zhao,* Shaochong Bu, He Teng, Jun Yang, Xiaomin Zhang, Xiaorong Li,* Lijie Dong* Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Medical University Eye Hospital, Tianjin, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiaorong Li; Lijie DongTianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Medical University Eye Hospital, No. 251 Fu Kang Road Nankai District, Tianjin 300384, People’s Republic of ChinaTel +86 22 23346430; Tel +86 1405326-6077Email xiaorli@163.com; aitaomubang@126.comBackground: Many studies have confirmed that high myopia is related to the high prevalence of cataracts, which results from apoptosis of lens epithelial cells (LECs) due to endoplasmic reticulum stress. Krüppel-like factor 6 (KLF6) is a tumor suppressor that is involved in the regulation of cell proliferation and apoptosis.Purpose: In this study, our purpose was to find the relationship between KLF6-induced apoptosis in LECs and ATF4 (activating transcription factor 4)-ATF3 (activating transcription factor 3)-CHOP (C/EBP homologous protein) signaling pathway.Methods: KLF6, ATF4, ATF3, and CHOP were ectopically expressed using cDNAs subcloned into the pCDNA3.1+ vector. ATF4, ATF3, and CHOP knockdown were performed by small interfering RNA (siRNA). Expression of relative gene was tested using QT-PCR and western-blot. Then, accompanied by UVB stimulation, cell viability was measured by CCK-8 assay; The cell damage was examined by live & dead staining; The apoptotic markers Bax and Bcl-2 were detected by immunoblotting; Quantitative apoptotic levels were measured with the Apoptosis Detection Kit; The expression level of reactive oxygen-free radical (ROS) was analyzed by DCFH-DA` probe.Results: Ectopically expressed ATF4, ATF3, and CHOP-induced apoptosis in cells, whereas ATF4, ATF3, and CHOP knockdown by small interfering RNA (siRNA) blocked KLF6-induced apoptosis. In addition, we determined that ATF4 regulates ATF3 and CHOP expression and that ATF3 silencing reduces CHOP upregulation without changing ATF4 levels; however, ATF4 and ATF3 expression was unaffected by blockade of CHOP, suggesting that KLF6 triggers endoplasmic reticulum stress in LECs by mediating the ATF4-ATF3/CHOP axis. Besides, KLF6 overexpression significantly induced LEC apoptosis under UV radiation, as demonstrated by the elevated Bax/Bcl-2 ratio.Conclusion: The ATF4-ATF3-CHOP pathway plays an important role in KLF6-induced apoptosis in HLECs. Our results increase our understanding of the mechanisms that regulate LEC apoptosis and contribute to the development of a new preventative strategy for cataract.Keywords: KLF6, ATF4, apoptosis, HLECs, endoplasmic reticulum stress

Recurrent neural networks (RNNs) are capable of learning features and long term dependencies from sequential and time series data and show outstanding performance in sequential modeling tasks. However, training process in RNNs is troubled by issues in learning processes such as slow inference, vanishing gradients and difficulties in capturing long term dependencies. In this paper, we introduce a new learning technique to update the weight set as we change the input sequence which is shifted by certain amount of time in training process, instead of using a traditional way to calculate one set of the weights and bias in training time series with sequences shifted by certain amount of time series. We also consider an algorithm for an evaluation process. In the traditional way, the evaluation process is executed by using final weights and biases calculated in the training process. Instead, during the testing process, the weights and biases are iteratively updated in each sequence as done in the training process. Several numerical experiments demonstrate the efficiency of the proposed techniques. [ABSTRACT FROM AUTHOR]