Enhancer RNAs (eRNAs) are demonstrated to be closely associated with tumourigenesis and cancer progression. However, the role of eRNAs in lung adenocarcinoma (LUAD) remains largely unclear. Thus, a comprehensive analysis was constructed to identify the key eRNAs, and to explore the clinical utility of the identified eRNAs in LUAD. First, LUAD expression profile data from the Cancer Genome Atlas (TCGA) dataset and eRNA-relevant information were integrated for Kaplan-Meier survival analysis and Spearman's correlation analysis to filtered the key candidate eRNAs that was associated with survival rate and their target genes in LUAD. Then, the key eRNA was selected for subsequent clinical correlation analysis. KEGG pathway enrichment analyses were undertaken to explore the potential signaling pathways of the key eRNA. Data from the human protein atlas (HPA) database were used to validate the outcomes and the quantitative real time-polymerase chain reaction (qRT-PCR) analysis was conducted to measure eRNA expreollectively, our results indicated that TBX5-AS1 may be a potential prognostic biomarker for LUAD patients and promote the targeted therapy of LUAD. Ebola Virus Disease (EVD) is a deadly and feared infectious disease, which can be responsible of debilitating physical and psychological sequelae in survivors including depression and anxiety disorders. Unfortunately, there are scarce data on survivor sequelae in Democratic Republic of the Congo. So this study assessed PTSD, depression and anxiety symptoms among EVD survivors enrolled in the follow-up program of the psychosocial care team of Beni town's general hospital. A cross-sectional study used consecutive sampling to recruit 144 Ebola virus disease survivors who came for follow up from October 23 to November 13; 2019. Basic socio-demographic data, presence of headache and short-term memory function were assessed. The Post-traumatic Checklist Scale and Hospital Anxiety and Depression Scale were used to assess psychological burden among participants. Descriptive statistics were used to summarized data and Pearson's or likelihood chi-square were used to test association between psychiatric disorders an teams fighting against EVD in the DRC.The prevalence of PTSD, depression and anxiety is high among EVD survivors. Development of specialized psychiatric services to sustain psychiatric and psychological health amongst survivors in the cultural context of the Eastern part of the DRC should be considered by the teams fighting against EVD in the DRC. In an abdominal symptom study in primary care in six European countries, 511 cases of cancer were recorded prospectively among 61,802 patients 16years and older in Norway, Denmark, Sweden, Netherlands, Belgium and Scotland. Colorectal cancer is one of the main types of cancer associated with abdominal symptoms; hence, an in-depth subgroup analysis of the 94 colorectal cancers was carried out in order to study variation in symptom presentation among cancers in different anatomical locations. Initial data capture was by completion of standardised forms containing closed questions about symptoms recorded during the consultation. Follow-up data were provided by the GP after diagnosis, based on medical record data made after the consultation. GPs also provided free text comments about the diagnostic procedure for individual patients. Fisher's exact test was used to analyse differences between groups. Almost all symptoms recorded could indicate colorectal cancer. 'Rectal bleeding' had a specificity of 99.4% antary information such as a positive FOBT or persistent symptoms may revise the PPV upwards. If a colorectal cancer is suspected by the GP despite few symptoms, the total clinical picture may still reach the NICE PPV threshold of 3% and justify a specific referral. Standard practice for conducting systematic reviews (SRs) is time consuming and involves the study team screening hundreds or thousands of citations. AGK2 mouse As the volume of medical literature grows, the citation set sizes and corresponding screening efforts increase. While larger team size and alternate screening methods have the potential to reduce workload and decrease SR completion times, it is unknown whether investigators adapt team size or methods in response to citation set sizes. Using a cross-sectional design, we sought to understand how citation set size impacts (1) the total number of authors or individuals contributing to screening and (2) screening methods. MEDLINE was searched in April 2019 for SRs on any health topic. A total of 1880 unique publications were identified and sorted into five citation set size categories (after deduplication) < 1,000, 1,001-2,500, 2,501-5,000, 5,001-10,000, and > 10,000. A random sample of 259 SRs were selected (~ 50 per category) for data extraction and analyts that with increasing citation set size, authors are less likely to adhere to gold-standard screening methods. It is possible that adjunct screening methods, such as crowdsourcing (large team) and computer-assisted technologies, may provide a viable solution for authors to complete their SRs in a timely manner.Large citation set sizes present a challenge to SR teams, especially when faced with time-sensitive health policy questions. Our study suggests that with increasing citation set size, authors are less likely to adhere to gold-standard screening methods. It is possible that adjunct screening methods, such as crowdsourcing (large team) and computer-assisted technologies, may provide a viable solution for authors to complete their SRs in a timely manner. To develop a regression neural network for the reconstruction of lesion probability maps on Magnetic Resonance Fingerprinting using echo-planar imaging (MRF-EPI) in addition to [Formula see text], [Formula see text], NAWM, and GM- probability maps. We performed MRF-EPI measurements in 42 patients with multiple sclerosis and 6 healthy volunteers along two sites. A U-net was trained to reconstruct the denoised and distortion corrected [Formula see text] and [Formula see text] maps, and to additionally generate NAWM-, GM-, and WM lesion probability maps. WM lesions were predicted with a dice coefficient of [Formula see text] and a lesion detection rate of [Formula see text] for a threshold of 33%. The network jointly enabled accurate [Formula see text] and [Formula see text] times with relative deviations of 5.2% and 5.1% and average dice coefficients of [Formula see text] and [Formula see text] for NAWM and GM after binarizing with a threshold of 80%. DL is a promising tool for the prediction of lesion probability maps in a fraction of time.