bluuebunny/crossref_metadata_2025_split huggingface dataset:
Noninvasive Identification of Core Gene Biomarkers in Patients with Acute Kidney Transplant Rejection
Authors: Zhao Huijia , Li Ling , Ye Qifa 
Published: November 2020

Abstract
Background: Acute rejection (AR) is one of common and critical complications after kidney transplantation, which gives rise to an increasing of allograft loss and even death. However, the potential mechanisms of AR remain incompletely understood at present. This study aimed to reveal the underlying mechanisms and identify core biomarkers of AR.Methods: The AR gene expression profile GSE1563 involving 6 renal transplant patients undergoing AR and 9 patients with well-functioning transplant with no clinical evidence of rejection was selected to analyze the differentially expressed genes (DEGs) from purified RNA of peripheral blood lymphocytes. DAVID was used to carry out Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A protein-protein interaction (PPI) network was built to display the interactions among these DEGs. To get further reliable significant genes and mechanisms, gene set enrichment analysis (GSEA) was applied to evaluate the hub gene analyzing via PPI network.Results: A total of 347 DEGs were captured, including 301 upregulated genes and 46 downregulated genes. Go and KEGG pathway analysis showed the DEGs were particularly enriched in immune response, inflammatory response to antigenic stimulus, RNA transport and protein stabilization. The PPI network indicated 3 modules were also mainly involved in immune response and RNA transport. 18 hub genes were selected in PPI network, among which there were 6 core genes evaluated by DAVID. By the way of GSEA, Oxidative stress was another potential mechanism besides immunity and ncRNA transport. Conclusion: Our analysis uncovered the immune response including humoral and cellular immunity, ncRNA transport as well as oxidative stress was the major mechanisms of AR associated respectively with MAPK8, CCL5, HMGB1, NCBP2, XPO1 and APP, which could be novel noninvasive biomarkers in peripheral blood for early diagnosis and could be helpful to the treatment of AR.
Identification of Hepatic Fibrosis Inhibitors Through Morphometry Analysis of Hepatic Multicellular Spheroids Models
Authors: Seo Haengran , Song Yeonhwa , Heo Jinyeong , Shum David , Lee Su-Yeon , Kim Sanghwa , Lee Minji , Kim A-Ram 
Published: November 2020

Abstract
Background: A chronic, local inflammatory milieu can cause tissue fibrosis that results in epithelial-to-mesenchymal transition (EMT), endothelial-to-mesenchymal transition (EndMT), increased abundance of fibroblasts, and further acceleration of fibrosis. Methods: In this study, we aimed to identify potential mechanisms and inhibitors of fibrosis using 3D model-based phenotypic screening. We established liver fibrosis models using multicellular tumor spheroids (MCTSs) composed of hepatocellular carcinoma (HCC) and stromal cells such as fibroblasts (WI38), hepatic stellate cells (LX2), and endothelial cells (HUVEC) seeded at constant ratios. Results: Through high-throughput screening of FDA-approved drugs, we identified retinoic acid and forskolin as candidates to attenuate the compactness of MCTSs as well as inhibit the expression of ECM-related proteins. Additionally, retinoic acid and forskolin induced reprogramming of fibroblast and cancer stem cells in the HCC microenvironment. Of interest, retinoic acid and forskolin had anti-fibrosis effects by decreasing expression of a-SMA and F-actin in LX2 cells and HUVEC cells. Moreover, when sorafenib was added along with retinoic acid and forskolin, apoptosis was increased, suggesting that anti-fibrosis drugs may improve tissue penetration to support the efficacy of anti-cancer drugs. Conclusion: Collectively, these findings support the potential utility of morphometric analyses of hepatic multicellular spheroid models in the development of new drugs with novel mechanisms for the treatment of hepatic fibrosis and HCCs.
Identification of mRNA-miRNA-lncRNA Competing Endogenous RNA&nbsp;Network in Adrenocortical Carcinoma Using Bioinformatics Analysis&nbsp;
Authors: Ye Senlin , Wang Haohui , Li Wei , Yi Lu 
Published: November 2020

Abstract
Background: Adrenocortical carcinoma (ACC) is a rare malignant tumor originating from the adrenal cortex. However, there are no eﬀective therapies to treat patients with ACC. LncRNA participates in a variety of biological processes of cancers. We constructed ceRNA network and identify key competing endogenous RNAs (ceRNAs) in adrenocortical carcinoma (ACC) using bioinformatic processing tools. Methods: Firstly, the differentially expressed genes (DEGs) were identified by analyzing GSE12368 and GSE19750 datasets. SangerBox was used to generate volcano maps. DAVID database was used for functional enrichment analysis. STRING database was used to conduct Protein-protein interaction (PPI) network, and hub genes were identified by Cytoscape plug-in CytoHubba. UCSC database was used to construct hierarchical clustering of hub genes. Upstream miRNAs of mRNAs were predicted by miRTarBase and upstream lncRNAs of miRNA by miRNet. Expression analysis for lncRNAs were performed via GEPIA. Prognostic analysis for genes, miRNAs and lncRNAs were performed via cBioPortal, OncomiR and GEPIA, respectively. Results: In this study, 49 and 276 upregulated and downregulated significant DEGs were identified. KEGG pathway enrichment analysis showed that they were significantly enriched in cancer-associated pathways. According to node degree, the top 10 upregulated genes and downregulated genes were classfied as hub genes. However, only 9 hub genes were defined as key genes because alteration was significantly associated with worse prognosis and all the 9 key genes were upregulated hub genes. Then, 15 miRNAs were predicted to target the 7 out of 9 key genes. But only 4 miRNAs were defined as key miRNAs because alteration significantly influenced prognosis in cancer. 185 lncRNAs were predicted to potentially interaction with the 4 miRNAs. Only 3 lncRNAs(XIST, HOXA11-AS and TMPO-AS1) were up-regulated and only 1 lncRNA (HOXA11-AS ) indicated alteration was significantly associated with worse prognosis in adrenocortical carcinoma. HOXA11-AS were finally identified as key lncRNA. Finally, RRM2-miR-24-3p/let-7a-5p-HOXA11-AS, CDK1/MCM4-miR-24-3P-HOXA11-AS competing endogenous RNA (ceRNA) sub-networks were constructed in adrenocortical carcinoma. Conclution：This study has constructed RRM2-miR-24-3p/let-7a-5p-HOXA11-AS, CDK1/MCM4-miR-24-3p-HOXA11-AS competing endogenous RNA (ceRNA) sub-networks. Our results suggested that these sub-networks might be potential therapeutic targets or prognostic biomarkers in ACC.
RANKL Immunisation Inhibits Prostate Cancer Metastasis by Modulating EMT Through A RANKL-Dependent Pathway
Authors: Park Mineon , Cho Yong Jin , Kim Bora , Ko Young Jong , Jang Yuria , Hyun Hoon , Lim Wonbong 
Published: November 2020

Abstract
Background: Prostate cancer (PCa) morbidity in the majority of patients is due to metastatic events, which are a clinical obstacle. Therefore, a better understanding of the mechanism underlying metastasis is imperative if we are to develop novel therapeutic strategies. Receptor activator of nuclear factor kappa-B (NF-κB) ligand (RANKL) regulates bone remodelling. RANKL was associated with epithelial-mesenchymal transition (EMT) and expression of metastasis-related genes in PC3 cells. Thus, agents that suppress RANKL signalling may be useful pharmacological treatments. Method: In this study, we proposed a strategy to induce anti-cytokine antibodies using mutant RANKL as an immunogen. Here, we used preclinical experimental models to investigate whether an inactive form of RANKL affects bone metastasis in RANKL-induced PCa.Results: RANKL activation was observed in human PCa tissue specimens. RANKL promoted migration and invasion of PC3 cells through EMT, and induced a significant increase in binding of β-catenin to TCF-4, an EMT-induced transcription factor in PCa cells, via mitogen-activated protein kinase and β-catenin/TCF-4 signalling. Thus, RANKL increased EMT and the metastatic properties of PC3 cells, suggesting a role as a therapeutic target to prevent PCa metastasis. Conclusion: Treatment with mutant RANKL reduced EMT and metastasis of PC3 PCa cells in an experimental metastasis model. Thus, mutant RANKL could serve as a potential vaccine to prevent and treat metastatic PCaTrial registration: Chosun University Hospital, CHOSUN 2020-06-001. Registered 01 June 2020-prospectevely registered, https://hosp.chosun.ac.kr/medi_depart/ site=hospital&mn=151&type=view&catename=IRB
Nanoscopic Quantification of Sub-mitochondrial Morphology, Mitophagy and Mitochondrial Dynamics in Patients With Mitochondrial Disease
Authors: Zou Weiwei , Chen Qixin , Slone Jesse , Yang Li , Lou Xiaoting , Diao Jiajie , Huang Taosheng 
Published: November 2020

Abstract
SLC25A46 mutations have been found to lead to mitochondrial hyper-fusion and reduced mitochondrial respiratory function, which results in optic atrophy, cerebellar atrophy, and other clinical symptoms of mitochondrial disease. However, it is generally believed that mitochondrial fusion is attributable to increased mitochondrial oxidative phosphorylation (OXPHOS)[1], which is inconsistent with the decreased OXPHOS of highly-fused mitochondria observed in previous studies. In this paper, we have used the live-cell nanoscope to observe and quantify the structure of mitochondrial cristae, and the behavior of mitochondria and lysosomes in patient-derived SLC25A46 mutant fibroblasts. The results show that the crista have been markedly damaged in the mutant fibroblasts, but that there is no corresponding increase in mitophagy. This study suggests that severely damaged mitochondrial cristae might be the predominant cause of reduced OXPHOS in SLC25A46 mutant fibroblasts. This study demonstrates the utility of nanoscope-based imaging for realizing the sub-mitochondrial morphology, mitophagy and mitochondrial dynamics in live cells, which may be particularly helpful for the quick assessment and diagnosis of mitochondrial abnormalities.
Where and how do young People Like to Get their Sexual and Reproductive Health Information? Experiences from Students in Higher Learning Institutions in Tanzania: A Cross-sectional Study
Authors: Mcharo Ruby Doryn , Mayaud Philippe , Msuya Sia Emmanueli 
Published: November 2020

Abstract
Background Sexual and reproductive health (SRH) among young adults in developing countries is still a major public health concern. Early school-based sexuality education programs and sexual health information sharing between teachers, parents and young people have been considered protective against sexual health risks that young people are prone to. There is limited information on preferred choices of “where” and “how” young people like to get their SRH information. Here, we describe what young people prefer to learn with regard to sexual matters, where and who they prefer to learn from, and their experiences of parent-child sexuality communication. MethodsThis was a cross-sectional study, conducted from March 2019 to January 2020 among students aged 18-24 years attending Higher Learning Institutions (HLIs) within Mbeya. A self-administered questionnaire was used to collect information on SRH education, ability to discuss sexual matters with a parent/guardian, and SRH information gap during early sexual experience. ResultsOut of 504 students that were enrolled, 377 (74.8%) reported to be sexually active with mean age at sexual debut of 18.4 years. Six out of ten students found it difficult to discuss or did not discuss sexual matters with a parent/guardian while growing up at age 12-18 years. Majority learnt about SRH matters from peers (30%) and lessons at schools (23%). We found a gender-biased preference on sexual matters discussions, such that female and male participants preferred discussions with female adults and male adults, respectively. Peers (18%), Media (17%) and schools (13%) were preferred sources of SRH information. On recalling first sexual experience, participants felt they needed to know more about sexual feelings, emotions and relationships (26.9%), safer sex (13.8%), how to be able to say 'No' (10.5%) and how to use a condom correctly (10.2%). ConclusionYoung people have a gender-biased preference when it comes to learning about SRH matters from their parents; however, such conversations seldom occur. Community health IEC should incorporate the agenda on building skills of parents on parent-child communication on sexual matters so as to empower them to confidently initiate and convey appropriate and sufficient sexual health information. Comprehensive SRH education and skills building is needed in the current school SRH curriculum in order need to meet the demand and needs of students’ and teachers’.
WITHDRAWN: Exploration and Augmentation of Pharmacological Space via Adversarial Auto-encoder Model for Facilitating Kinase-centric Drug Development
Authors: Bai Xinyu , Yin Yuxin 
Published: November 2020

Abstract
Predicting drug-protein interactions (DPIs) is of great importance for drug discovery and repositioning, yet still challenging mainly due to the sparse nature of DPI matrixes, resulting in poor generalization performance. Hence, unlike typical DPI prediction models which focused on representation learning or model selection, we propose a deep neural network-based strategy, PCM_AAE, that re-explores and augments the pharmacological space of kinase inhibitors by introducing adversarial auto-encoder model (AAE) to improve the generalization of the prediction model. To complete the pharmacological space, we constructed Ensemble of PCM-AAE (EPA), an ensemble model that quickly and accurately yields quantitative predictions of binding affinity between any human kinase and inhibitor. In rigorous internal validation, EPA showed excellent performance, consistently outperforming the model trained with the imbalanced set, especially for targets with relatively fewer training data points. Improved prediction accuracy of EPA to external datasets again demonstrated enhanced generalization ability of EPA that could gracefully handle previously unseen kinases or inhibitors. Further analysis showed promising potential when EPA was directly applied to virtual screening and off-target prediction, exhibiting the practicality of the EPA model in hit prediction. Our strategy is expected to facilitate kinase-centric drug development, as well as to solve more challenging prediction problems with insufficient data points.
Experimental investigation into the anode erosion phenomenon in a DC non-transferred arc plasma torch
Authors: Sun Qiang , Liu Yonghong , Zhu Yejun , Han Yancong 
Published: November 2020

Abstract
Anode erosion phenomenon in a DC non-transferred arc plasma torch was experimentally investigated. Anode weight loss and anode erosion position with changes in plasma current, gas-flow rate and anode length were studied. The results show that all these influences could be explained by plasma power. Anode erosion position was closely related to the structure of anode nozzle and the working conditions of plasma torch. The influence of anode arc root position and the energy flow through it on anode erosion was also analyzed. Moreover, the mechanism of anode erosion and its influence on plasma jet were studied. The results can serve as a reference for revealing the mechanism of plasma discharge, for the optimization design of arc plasma torch, and for high-quality plasma generation.
A decision tree model for evaluating the cost effectiveness of Single-Photon Emission-Computed Tomography compared with stress echocardiography for diagnosis of coronary artery disease
Authors: Javan-Noughabi Javad , Rezapour Aziz , Hajahmadi Marjan , Alipour Vahid , Jafari Abdosaleh , Faramarzi Ahmad 
Published: November 2020

Abstract
Background Early diagnosis of coronary artery disease is very vital for success in treatment of this disease. However, the appropriate diagnostic modality for diagnosis of coronary artery disease is uncertain. Therefore, we conducted this study to compare the cost-effectiveness of Single-Photon Emission-Computed Tomography (SPECT) versus stress echocardiography for diagnosis of coronary artery disease in Iran.Methods A decision tree model was developed to compare the cost-effectiveness of SPECT versus stress echocardiography. This study was conducted in Tehran, capital of Iran, between April 1, 2017, and September 1, 2018. The cost analysis was conducted from a societal perspective and medical direct costs, nonmedical direct costs and indirect costs were estimated.. Effectiveness was defined as the accurate detection of coronary artery disease and invasive coronary angiography was used as a gold standard. The incremental cost-effectiveness ratio was defined as an additional cost per correct diagnosis.Results SPECT was associated with higher costs and lower effectiveness compared with stress echocardiography. Therefore stress echocardiography is dominant alternative compared to SPECT. The results also indicated that total cost per patient were $970.49 and $781.8 for SPECT and stress echocardiography, respectively. Also, the percent of true positive and true negative responses were %88 and %79 for SPECT and %90 and %92 for stress echocardiography.Conclusions The results of this study indicate that stress echocardiography is the cost-effective modality in the diagnosis of coronary artery disease compared with SPECT. According to the results, it is suggested cardiologists use stress echocardiography instead of SPECT for the diagnosis of coronary artery disease. The result of the current study has significant concepts for decision-making in designing clinical guidelines for the diagnosis of coronary artery disease.
Diabetes mellitus is associated with lower mortality in intensive care unit: a multicenter historical cohort study
Authors: Hu Chang , Hu Bo , Wang Jing , Peng Zhiyong , Kashani Kianoush B. , Li Jianguo 
Published: November 2020

Abstract
Background: The association of pre-existing diabetes mellitus and outcomes among critically ill patients remains unknown.Methods: This retrospective study enrolled patients who were covered by the eICU Collaborative Research Database from 2014 to 2015. DM was the exposure of interest, and diabetic individuals were adjudicated by the medical history, and blood glucose level (BGL). We abstracted basic characteristics, laboratory variables, and primary exposures. ICU mortality was the primary outcome.Results: In a cohort of 134,429 critically ill patients (male 54.4%, median age 66 [54-77] years, BMI 28[24-33] kg/m2), the prevalence of DM was 29%. In comparison with nondiabetics, DM patients were older, more obese, had higher Acute Physiology and Chronic Health Evaluation (APACHE)-IV score, and ICU admission BGL. In comparison with nondiabetics, pre-existing DM was associated with lower ICU mortality (OR: 0.846, 95%CI: 0.791-0.905). In multivariable logistic regression and Cox proportional hazard analyses, pre-existing DM was associated with decreased odds of ICU mortality in hyperglycemic patients (>163 mg/dL), higher APACHE IV score (>67), middle to old age (45-75 years), sepsis and morbid obesity (BMI>35 kg/m2). Also, in comparison with nondiabetics, pre-existing DM was associated with lower mortality among those with higher mean BGL (>128 mg/dL), and higher mortality in lower mean BGL (<107 mg/dL). Conclusions: In comparison with nondiabetics, pre-existing DM is associated with a lower adjusted ICU mortality. This association is stronger in DM patients with hyperglycemia, obesity, sepsis, middle to old age, and higher APACHE IV score.
Machine Learning Based Predictors for COVID-19 Disease Severity
Authors: Patel Dhruv , Kher Vikram , Desai Bhushan , Lei Xiaomeng , Cen Steven , Nanda Neha , Gholamrezanezhad Ali , Duddalwar Vinay , Varghese Bino , Oberai Assad A 
Published: November 2020

Abstract
Predictors of the need for intensive care and mechanical ventilation can help healthcare systems in planning for surge capacity for COVID-19. We used socio-demographic data, clinical data, and blood panel profile data at the time of initial presentation to develop machine learning algorithms for predicting the need for intensive care and mechanical ventilation. Among the algorithms considered, the Random Forest classifier performed the best with AUC = 0.80 for predicting ICU need and AUC = 0.82 for predicting the need for mechanical ventilation. We also determined the most influential features in making this prediction, and concluded that all three categories of data are important. Finally, we determined the relative importance of blood panel profile data and noted that the AUC dropped by 0.12 units when this data was not included, thus indicating that it provided valuable data in predicting disease severity.
Development and validity of the Korean Psychiatric Triage Algorithm
Authors: Ha Jeongmin , Jang Kyeongmin , An Misuk 
Published: November 2020

Abstract
Background Psychiatric triage algorithm can improve the quality of care by providing a systematic method for classifying the severity of patients experiencing psychiatric crisis in the emergency room and by determining the optimal time frame for intervention. The aim of the present study was to test the professional validity and clinical validity of a psychiatric triage algorithm developed for use in South Korea.Methods The initial algorithm was developed through systematic literature review. Its validity was then verified by 10 experts. Based on results of expert validity, the algorithm was modified and the final algorithm was developed.Results Its clinical validity was then verified by 30 emergency room nurses who had used triage. Four questions of expert validity results with a CVI of 0.8 or less were revised to reflect expert opinion. The clinical validity of the final modified algorithm was 2.9 ~ 3.47.Conclusion The use of highly validity psychiatric triage algorithm by ER (Emergency Room) nurses not only can improve the quality of care, but also can improve patient outcomes and experience.