bluuebunny/crossref_metadata_2025_split huggingface dataset:
The&nbsp;Association&nbsp;Between&nbsp;Age at Diagnosis of Type 2 Diabetes and Albuminuria&nbsp;in Chinese Adults
Authors: Wu Shujing , Liu Shanshan , Zhao Zhiyun , Li Mian , Wang Tiange , Wang Shuangyuan , Xu Min , Chen Yuhong , Dai Meng , Zhang Di , Yu Xuefeng , Tang Xulei , Hu Ruying , Ye Zhen , Shi Lixin , Su Qing , Yan Li , Qin Guijun , Wan Qin , Chen Gang , Gao Zhengnan , Wang Guixia , Shen Feixia , Luo Zuojie , Qin Yingfen , Chen Li , Huo Yanan , Li Qiang , Zhang Yinfei , Liu Chao , Wang Youmin , Wu Shengli , Yang Tao , Deng Huacong , Chen Lulu , Zhao Jiajun , Mu Yiming , Xu Yiping , Bi Yufang , Lu Jieli , Xu Yu , Wang Weiqing , Ning Guang 
Published: November 2020

Abstract
Background: Type 2 diabetes is increasingly diagnosed at a younger age worldwide and in China. Limited data are available regarding the association between age at diabetes diagnosis and risks of albuminuria, which is a common microvascular complication in diabetes patients. In addition, few studies on age at diagnosis and outcomes have fully accounted for the complex interplay between age at diagnosis and the actual age or diabetes duration, all of which are independently associated with vascular risks.Methods: We used data from a nationwide multicenter study with 207,961 participants recruited from 25 communities across mainland China during 2010-2012. Age, sex, and study sites were matched for 31,366 screen-detected type 2 diabetes and 31,366 normal controls. Age, sex, study sites, and diabetes duration were matched for 7,490 self-reported type 2 diabetes and 7,490 normal controls. Risks of having albuminuria in matched type 2 diabetes vs. normal controls were examined using multivariable logistic regression analysis in strata of age at type 2 diabetes diagnosis (<50, 50-59, 60-69, or ≥70 years). Albuminuria was defined as urinary albumin-to-creatinine ratio ≥30 mg/g.Results: Percentages of albuminuria were significantly higher among type 2 diabetes patients compared with normal controls in each stratum of age at diagnosis. Although the absolute rate of albuminuria is higher in older adults, the odds ratio of albuminuria in type 2 diabetes vs. matched controls decreased with increasing age at diagnosis. For participants with diabetes diagnosed at an age of <50, 50-59, 60-69, or ≥70 years, the multivariable adjusted risk of albuminuria increased by 81%, 60%, 45%, and 33% for screen-detected diabetes, and 135%, 121%, 90%, and 58% for self-reported diabetes compared with their normal controls, respectively. Conclusions: A younger age at diagnosis of type 2 diabetes is associated with a more significantly elevated risk of albuminuria than an older age at diagnosis in Chinese adults.
Identification of the Genetic Basis for the Large-tailed Phenotypic Trait in Han Sheep Through Integrated mRNA&nbsp;and miRNA&nbsp;Analysis of Tail Fat Tissue Samples
Authors: Guangli Yang , Huan Zhang , Shuhong Zhang , Zhiqiang Li , Fengyi Gao , Guan Wang , Qiankun Wang , Xiangyu Li , Yongfeng Yan , Ming Li 
Published: November 2020

Abstract
Background: While evolution has led certain breeds of sheep to exhibit large tails composed of fatty tissue, the genetic basis for this fatty large-tailed phenotypic trait remains to be defined in breeds of Han sheep. Here, we employed a high-throughput sequencing approach to identify mRNAs and microRNAs (miRNAs) that were differentially expressed in tail fat tissue samples from large-tailed Han (LTH) and small-tailed Han (STH) sheep in order to identify key genetic determinants of the large-tailed phenotype.Results: In total, we identified 521 mRNAs (237 upregulated, 284 downregulated) and 14 miRNAs (6 upregulated, 8 downregulated) that were differentially expressed between these two sheep breeds. Predictive analytical database tools were subsequently utilized to identify 2,409 putative targets of these differentially expressed miRNAs (DEMs), including 65 which were among the list of differentially expressed genes (DEGs) identified in the present study. By specifically focusing on predicted DEM/DEG pairs with appropriate regulatory directionality, we identified DIRF, HSD17B12, LPL, APOBR, INSIGI, THRSP, ACSL5, FAAH, ACSS2, APOA1, ACLY, and ACSM3 through mRNA analyses and ACSL4, FTO, FGF8, IGF2, GNPDA2, LIPG, PRKAA2, ELOVL7, SOAT2, and SIRT1 through miRNA analyses as candidate genes which may regulate fat deposition and fatty acid metabolism in the adipose tissue from the tails of Han sheep. Conclusion: Together, our data provide insight into the potential genetic basis for the large-tailed phenotype of LTH sheep, suggesting that it may be attributable to specific DEMs and DEGs that regulate one another and thereby control lipid metabolism. These data provide a basis for future research regarding the role of these genes in ovine tail fat deposition, and offer preliminary perspectives on the molecular mechanisms governing the fatty large-tailed phenotype in LTH sheep.
Exploring the Effects of Changping Decoction on Irritable Bowel Syndrome by Pathway and Pharmacology Network Bioinformatics Analysis
Authors: Hu Guo-Jie , Li Ding , Li Shi-Fang , Li Xiao-Yuan , Sun Xiao-Wei , Sun Tian-Yue 
Published: November 2020

Abstract
Background An increasing body of research has confirmed the effectiveness of Traditional Chinese Medicine (TCM) for the treatment of irritable bowel syndrome (IBS).Methods We explored the potential mechanism of Changping decoction (CPD) in the treatment of IBS through pathway analysis based on a network pharmacology approach. Public databases, including the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Gene Expression Omnibus, and STRING, were used to screen the active ingredients and targets of CPD. Enrichment analysis was performed using the R-3.6.0 software to expound the biological functions and related pathways of CPD targets. The Cytoscape software was used to construct a “disease-CPD-target” network and identify hub genes of CPD relevant for the treatment of IBS. Employing rat models, pathological observation and abdominal withdrawal reflex tests were used to verify the effectiveness of CPD in the treatment of IBS. Immunohistochemistry was used to confirm the relationship between the CPD treatment and hub genes.Results Network pharmacological analysis of CPD for the treatment of IBS identified 159 active ingredients. A total of 118 key targets were identified, including MAPK8, VEGFA, PTGS2, and others. A series of signaling pathways, such as MAPK, Kaposi sarcoma-associated herpesvirus infection, and IL-17 signaling pathway were found to play an important role in the therapeutic mechanism of CPD in the treatment of IBS. Pathological observation and abdominal withdrawal reflex tests confirmed that the symptoms of IBS in rats were relieved by CPD. Moreover, immunohistochemistry confirmed that CPD could inhibit the expression of inflammation-associated factors, such as VEGFA, MAPK8, and PTGS2.Conclusions Based on network pharmacology analysis, the present study provides insights into the potential mechanism of CPD in the treatment of IBS after successfully screening for associated key target genes and signaling pathways. These findings establish a theoretical basis for the development of CPD-derived therapeutics.
WITHDRAWN: Network Pharmacology-based to Investigate Pharmacological Mechanisms of Active Ingredients in Gegen Qinlian Pill to Ameliorate Irinotecan-induced Diarrhea
Authors: Wu Yihan , Cheng Yanfen , Yang Yuhan , Wang Di , Yang Xiaoqin , Fu Chaomei , Zhang Jinming , Hu Yichen 
Published: November 2020

Abstract
Background: The application of natural extracts or compounds derived from Chinese medicine is deemed to a promising strategy to prevent irinotecan (CPT-11)-induced gut toxicity. Based on the protective activity of Gegen Qinlian decoction in our previous study, we speculated that Gegen Qinlian Pill (GQP) would exhibit similar therapeutic effects. However, the effective material basis and the potential mechanisms underlying the effect of GQP in the treatment of diarrhea induced by CPT-11 have not been fully elucidated. Herein, we primarily investigated amelioration effect of GQP on the CPT-11 induced gut toxicity, and further explore its anti-diarrhea mechanism.Methods: Firstly, the protective effect of GQP towards alleviating diarrhea in mice following CPT-11 administration was investigated. Furthermore, the effective ingredients of GQP in serum sample of mice by HPLC-Q-TOF-MS analysis was obtained. Next, based on these active components, an interaction network linking “compound-target-pathway” was established. Finally, a predicted mechanism within vivo validation of GQP based on Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were obtained. Results: A total of 19 chemical compounds derived from the GQP were identified in its serum sample. Then, an interaction network linking “compound-target-pathway” was established to illuminate the interaction between these components absorbed into serum and their targets for diarrhea. GQP exerted a curative effect on diarrhea and diarrhea-related diseases by targeting different targets, regulating inflammation, oxidative stress, and proliferation processes. Conclusion: Taken together, this study provides a novel and scientific strategy to discover the potential effective constituents of herbs or herbal formula, and elucidated basic pharmacological effects and underlying mechanisms of GQP in the treatment of CPT-11 induced gut toxicity.
Development of A Novel Anti-Liver Fibrosis Formula with luteolin, licochalcone A, aloe-emodin and acacetin by network pharmacology and transcriptomics analysis
Authors: Zhou Yuan , Wu Rong , Cai Fei-Fei , Zhou Wen-Jun , Lu Yi-Yu , Zhang Hui , Chen Qi-Long , Sun Mingyu , Shi-Bing Su 
Published: November 2020

Abstract
Background: Liver fibrosis leads to loss of liver function. Xiaoyaosan decoction (XYS) as a classical Traditional Chinese Medicine (TCM) formula is used to treatment liver fibrosis in clinical and alleviated CCl4-induced liver fibrosis in our previous study.Xiaoyaosan decoction was composed of many ingredients, and the active ingredients is not clear. The Aim of this study is to explore the clarified compounds or compound combinations to treat liver fibrosis.Methods: Network pharmacology combined with transcriptomics analysis were used to analyze the Xiaoyaosan decoction (XYS) and liver depression and spleen deficiency syndrome liver fibrosis. This consisted constructed XYS-Syndrome-liver fibrosis network, the predict formula named LLAAF was develop from the network by topological analysis according to network stability. The anti-fibrosis effect was evaluated by in vitro and in vivo study.Results: According to the network XYS-Syndrome-liver fibrosis network, luteolin, licochalcone A, aloe-emodin, and acacetin formula (LLAAF) was predicted from 8 key compounds and 255 combinations in XYS, and LLAAF had a synergistic effect on the proliferation inhibition of hepatic stellate cells (HSCs) compared to each individual compound alone. The treatment of XYS and LLAAF showed a similar anti-liver fibrotic effect that reduced histopathological changes of liver fibrosis, Hyp content and levels of α-SMA and collagen I in CCl4-induced liver fibrosis in rat. Transcriptomics analysis revealed LLAAF regulated PI3K-Akt, AMPK, FoxO, Jak-STAT3, P53, cell cycle, focal adhesion, and PPAR signaling. Furthermore, LLAAF was confirmed to regulate Jak-STAT and PI3K-Akt-FoxO signaling in vitro and in vivo.Conclusions: This study developed a novel anti-liver formula, LLAAF from XYS demonstrated the anti-liver fibrotic activity may be involved in the regulation of Jak-STAT and PI3K-Akt-FoxO signaling.
Class Center-Based Firefly Algorithm for Handling Missing Data
Authors: Nugroho Heru , Utama Nugraha Priya , Surendro Kridanto 
Published: November 2020

Abstract
Estimating missing data in a dataset is a significant advance during the data cleaning stage. Improper data handling can make inaccurate results when conducting data analysis. Most of the research about missing data estimation is irrespective of the correlation between attributes. However, an adaptive search procedure helps find the estimates of the missing data when correlations between attributes are considered in the process. Firefly Algorithm (FA) implements an adaptive search procedure in the imputation of the missing data by finding the estimated value that is closest to the value in other data known. Therefore, this study proposes a class center-based adaptive approach model for missing data by considering the attribute correlation in the imputation process (C3-FA). Based on the experiment, the general result find that the class center-based firefly algorithm is an efficient technique for getting the actual value in handling the missing data. This can be seen on the value of Pearson correlation coefficient (r) that close to 1 and the root mean squared error (RMSE) value is generally closer to 0. In addition, the proposed method can maintain the true distribution of data values. This is indicated by the Kolmogorov–Smirnov test that value of DKS for most of the attributes in the dataset is generally closer to 0. Also, the results of the accuracy evaluation using three classifiers, showed that the proposed method produces good accuracy.
User Profile Correlation-Based Similarity Algorithm in Movie Recommendation System
Authors: Widiyaningtyas Triyanna , Hidayah Indriana , Adji Teguh Bharata 
Published: November 2020

Abstract
A recommendation system is a software used in the e-commerce field that provides recommendations for customers to choose the items they like. Several recommendation systems have been proposed; however, collaborative filtering is the most widely used approach. The main issue in collaborative filtering is how to implement a similarity algorithm that can improve performance in the recommendation system. Several similarity algorithms based on user rating value have been developed, and recently a similarity algorithm has been developed that combines the user rating value and the user behavior value. However, the existing research is still based only on a single user behavior value, which is the genre data. Therefore, we propose a new similarity algorithm that considers not only the genre data but also the user profile data (namely age, gender, occupation, and location). The new similarity we are proposing is called User Profile Correlation-based Similarity (UPCSim). The user profile correlation similarity was obtained by calculating the correlation coefficient between the user profile data and the user rating or behavior values. An experiment was done to compare the accuracy of the UPCSim algorithm with that of the previous algorithm. The experiment results show that the UPCSim algorithm can improve the recommendation performance MAE by 1.64% and RMSE by 1.4% compared to the previous algorithm.
The Holistic Health Status of Chinese Homosexual and Bisexual Adults: A Scoping Review Protocol
Authors: Wu Chanchan , Choi Edmond Pui Hang , Chau Pui Hing , Choi Kitty Wai Ying 
Published: November 2020

Abstract
Background: There is a considerable number of homosexual and bisexual people in the Chinese population, while their health conditions have not received sufficient attention compared with general Chinese. Referring to World Health Organization (WHO)’s definition, holistic health is a comprehensive concept incorporating physical, mental, and social well-being. However, existing research seems inadequate and unbalanced on the holistic health of this population, especially many studies only focus on sexually transmitted infections (STI) and relating preventions. Apart from these, the health status of these sexual minorities from a holistic perspective remains unclear. Therefore, this scoping review aims to comprehensively examine all available literature and will be the first to map the existing evidence on the holistic health of homosexual and bisexual Chinese.Methods: This proposed scoping review has been structured according to the Joanna Briggs Institute (JBI) recommended framework, which was proposed by Arksey and O’Malley and further enhanced by Levac, et al. Pilot searches of PubMed in English and SinoMed in Chinese were completed to identify all relevant search terms or keywords, then a comprehensive search strategy has been carried out across all relevant databases centering on health care, psychology, nursing and social science, including both English and traditional as well as simplified Chinese electronic databases. Screening and study selection will be independently conducted by two reviewers, and consulting a third senior reviewer based on consensus needs. Data will be extracted using a structured data form referring to the Cochrane template, and a narrative synthesis of the findings will be used.Discussion: There is no systematically reviewed evidence available or underway review on the holistic health of either homosexual or bisexual Chinese, so this scoping review will serve as a most comprehensive way to map the existing evidence and draw a big picture of their health conditions. Results of this review can be used to inform scholars of existing health issues and other major needs, then to provide scientific references for the development of person-centered culturally sensitive programs with Chinese characteristics.Systematic review registration: This protocol has been registered within Open Science Framework (https://osf.io/82r7z) on April 27, 2020.
A Randomized, Controlled Study on the Safety and Efficacy of Maraviroc and/or Favipiravir vs Currently Used Therapy in Severe COVID-19 Adults. “COMVIVIR” Trial.
Authors: Pérez-García Adolfo , Villalobos-Osnaya Alma , Hernández-Medel Maria Luisa , Perez-Navarro Lucia Monserrat , Medina-Hernandez Elba O. , Cabrera-Orejuela Diana Sofia , Espinoza-Garcia Ana Maria , Solleiro-Villavicencio Helena , Leon-Hernandez Mireya , Mayor Arianna Rodriguez-Cal Y , Servin-Murillo Manli M. , Carrillo-Ruiz Jose Damian , Serrano-Loyola Raul , Guerrero-Avendaño Guadalupe Mercedes Lucia , Reyes-Teran Gustavo , Sierra-Madero Juan , de Oca Gonzalo Salgado-Montes , Avila-Rios Santiago , Lopez-Alvarenga Juan Carlos , Hernandez-Ruiz Joselin , Mummidi Srinivas 
Published: November 2020

Abstract
Multiple studies have established that hyperinflammatory response induced by SARS CoV-2 is a main cause of complications and death in infected subjects. Such dysfunctional immune response has been described as a dysregulated and exacerbated production of cytokines and chemokines that attracts and activates inflammatory cells, which start and sustain pulmonary and systemic damage, thus causing complications that lead to multi organ failure and death. Therefore, we suggest that blocking key inflammation receptors could help to reduce migration and activation of T cells, monocytes/macrophages and neutrophils, thus mitigating the cytokine dysregulation and averting severe complications and death. Importantly, the optimum treatment for COVID-19 severe patients should combine a modulator of the immune response plus a direct antiviral drug against SARS-CoV-2, in order to address both the hyperinflammatory effects of the immune dysregulation and the viral load. Methods: Maraviroc (MVC), a CCR5 antagonist, and Favipiravir (FPV), an antiviral, will be evaluated single and combined, added to the treatment currently used at the Hospital General de México Dr. Eduardo Liceaga for severe COVID-19 patients. One hundred patients will be allocated in four arms [Current treatment only (CT), CT+MVC, CT+FPV, CT+MVC+FPV]. Percentage of patients free of mechanical ventilation or death at day 28, immunophenotyping and viral load will be compared between groups. Discussion: New immune focused therapies are targeting strong inflammation mediators such as IL-6 and IL1-β; nevertheless, to our best knowledge, only one study explores chemotaxis control. The use of a drug therapy that addresses both the regulation of the immune response and the inhibition of viral replication could at the same time, help to alleviate the hyperinflammatory condition and reduce the time of the viral clearance process, therefore improving treatment outcomes.
Flame: An Open Source Framework for Model Development, Hosting, and Usage in Production Environments
Authors: Pastor Manuel , Gómez-Tamayo José Carlos , Sanz Ferran 
Published: November 2020

Abstract
This article describes Flame, an open source software for building predictive models and supporting their use in production environments. Flame is a web application, with a Python backend and a web-based graphic interface, which can be used as a desktop application or installed in a server receiving requests from multiple users. Models can be built starting from any collection of biologically annotated chemical structures, since the software supports structural normalization, molecular descriptor generation and machine learning building, using predefined workflows. The model building workflow can be customized from the graphic interface, selecting the type of normalization, molecular descriptors, and machine learning algorithm to be used from a panel of state-of-the-art methods implemented natively. Moreover, Flame implements a mechanism allowing to extend its source code adding unlimited model customization. Models generated with Flame can be easily exported facilitating collaborative model development. All models are stored in a persistent model repository supporting model versioning. Models are identified by unique model IDs and include detailed documentation formatted using widely accepted standards. The current version is the result of nearly three years of development in collaboration with users from pharmaceutical industry within the IMI eTRANSAFE project, which aims, among other objectives, to develop high quality predictive models based on shared legacy data for assessing the safety of drug candidates.