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eation of a supportive environment may be helpful.BACKGROUND Adverse drug events (ADEs) often occur as a result of drug-drug interactions (DDIs). The use of data mining for detecting effects of drug combinations on ADE has attracted growing attention and interest, however, most studies focused on analyzing pairwise DDIs. Recent efforts have been made to explore the directional relationships among high-dimensional drug combinations and have shown effectiveness on prediction of ADE risk. However, the existing approaches become inefficient from both computational and illustrative perspectives when considering more than three drugs. METHODS We proposed an efficient approach to estimate the directional effects of high-order DDIs through frequent itemset mining, and further developed a novel visualization method to organize and present the high-order directional DDI effects involving more than three drugs in an interactive, concise and comprehensive manner. We demonstrated its performance by mining the directional DDIs associated with myopathy using a publicly ava and ultimately impact patient health care. AVAILABILITY AND IMPLEMENTATION http//lishenlab.com/d3i/explorer.html.BACKGROUND To evaluate if United States Medical Licensing Examination (USMLE) Step 1, USMLE Step 2 CK, USMLE Step 3, and residency third-year in-service training exam (ITE) scores predict the results of American Board of Internal Medicine Certifying Exam (ABIM-CE). METHODS We performed a retrospective review of USMLE Step 1, USMLE Step 2 CK, USMLE Step 3, third-year residency ITE scores and ABIM-CE results of IM residents at our residency program from 2004 through 2017. Statistical analysis was perfrormed using Pearson correlation coefficient, and logistic regression to assess the relationship between USMLE Step 1, USMLE Step 2CK, USMLE Step 3, 3rd year ITE scores and ABIM-CE results. We used Multivariate logistic regression to predict pass or fail results in ABIM-CE based on USMLE and third-year ITE test scores controlling for other covariates. RESULTS Among 114 Internal Medicine MD residents included in the study, 92% (n = 105) passed the ABIM-CE. The OR of passing ABIM-CE was 2.70 (95% CI = 1.38-5.29), 2.3compared to USMLE Step 1 and USMLE Step 2 scores. USMLE Step 1 scores more predictive of ABIM-CE results compared to USMLE Step 2CK scores. Thus, residency programs can identify internal medicine residents at risk of failing ABIM-CE and formulate interventions at an early stage during residency training. Measures such as enrolling them in question banks or board review courses can be helpful in improving their chances of passing ABIM-CE.BACKGROUND The key to modern drug discovery is to find, identify and prepare drug molecular targets. However, due to the influence of throughput, precision and cost, traditional experimental methods are difficult to be widely used to infer these potential Drug-Target Interactions (DTIs). Therefore, it is urgent to develop effective computational methods to validate the interaction between drugs and target. METHODS We developed a deep learning-based model for DTIs prediction. The proteins evolutionary features are extracted via Position Specific Scoring Matrix (PSSM) and Legendre Moment (LM) and associated with drugs molecular substructure fingerprints to form feature vectors of drug-target pairs. Then we utilized the Sparse Principal Component Analysis (SPCA) to compress the features of drugs and proteins into a uniform vector space. Lastly, the deep long short-term memory (DeepLSTM) was constructed for carrying out prediction. RESULTS A significant improvement in DTIs prediction performance can be observed on experimental results, with AUC of 0.9951, 0.9705, 0.9951, 0.9206, respectively, on four classes important drug-target datasets. Further experiments preliminary proves that the proposed characterization scheme has great advantage on feature expression and recognition. We also have shown that the proposed method can work well with small dataset. CONCLUSION The results demonstration that the proposed approach has a great advantage over state-of-the-art drug-target predictor. To the best of our knowledge, this study first tests the potential of deep learning method with memory and Turing completeness in DTIs prediction.BACKGROUND Despite the potential of digital health interventions to improve the delivery of psychoeducation to people with mental health problems and their relatives, and substantial investment in their development, there is little evidence of successful implementation into clinical practice. We report the first implementation study of a digital health intervention Relatives Education And Coping Toolkit (REACT), into routine mental healthcare. Homoharringtonine solubility dmso Our main aim was to identify critical factors affecting staff uptake and use of this online self-management tool for relatives of people with psychosis or bipolar. METHODS A mixed-methods, theory-driven (Normalisation Process Theory), iterative multiple case study approach using qualitative analysis of interviews with staff and quantitative reporting of uptake. Carer researchers were part of the research team. RESULTS In all, 281 staff and 159 relatives from Early Intervention teams across six catchment areas (cases) in England registered on REACT; 129 staff took part iequate mobile technologies. Wider contextual factors including adequate funding for mental health services and prioritisation of carer support, also need to be addressed for successful implementation of carer focussed digital interventions. TRIAL REGISTRATION Study registration ISCTRN 16267685.BACKGROUND During the process of decision-making for long-term care, clients are often dependent on informal support and available information about quality ratings of care services. However, clients do not take ratings into account when considering preferred care, and need assistance to understand their preferences. A tool to elicit preferences for long-term care could be beneficial. Therefore, the aim of this qualitative descriptive study is to understand the user requirements and develop a web-based preference elicitation tool for clients in need of long-term care. METHODS We applied a user-centred design in which end-users influence the development of the tool. The included end-users were clients, relatives, and healthcare professionals. Data collection took place between November 2017 and March 2018 by means of meetings with the development team consisting of four users, walkthrough interviews with 21 individual users, video-audio recordings, field notes, and observations during the use of the tool. Data were collected during three phases of iteration Look and feel, Navigation, and Content. A deductive and inductive content analysis approach was used for data analysis. RESULTS The layout was considered accessible and easy during the Look and feel phase, and users asked for neutral images. Users found navigation easy, and expressed the need for concise and shorter text blocks. Users reached consensus about the categories of preferences, wished to adjust the content with propositions about well-being, and discussed linguistic difficulties. CONCLUSION By incorporating the requirements of end-users, the user-centred design proved to be useful in progressing from the prototype to the finalized tool ‘What matters to me’. This tool may assist the elicitation of client’s preferences in their search for long-term care.BACKGROUND In order to organize person-centered health services for a growing number of people with multiple complex health and social care needs, a shift from fragmented to integrated health services delivery has to take place. For the organization of governance in integrated health services, it is important to better understand the underlying factors that drive collaboration, decision-making and behavior between individuals and organizations. Therefore, this article focuses on these underlying normative aspects of integrated health services. This study investigates the values that underpin integrated health services delivery as a concept, by examining the extent to which an initial literature based set of underlying values underpins integrated care and the relevance of these values on the different levels of integration. METHODS An international Delphi study with 33 experts from 13 different countries was carried out to examine the initial set of underlying values of integrated health services. In addition,the relationship between normative integration and governance, and differences between the value priorities of stakeholder groups.BACKGROUND Blood-retinal barrier cells are known to exhibit a massive phenotypic change during experimental autoimmune uveitis (EAU) development. In an attempt to investigate the mechanisms of blood-retinal barrier (BRB) breakdown at a global level, we studied the gene regulation of total retinal cells and retinal endothelial cells during non-infectious uveitis. METHODS Retinal endothelial cells were isolated by flow cytometry either in Tie2-GFP mice (CD31+ CD45- GFP+ cells), or in wild type C57BL/6 mice (CD31+ CD45- endoglin+ cells). EAU was induced in C57BL/6 mice by adoptive transfer of IRBP1-20-specific T cells. Total retinal cells and retinal endothelial cells from naïve and EAU mice were sorted and their gene expression compared by RNA-Seq. Protein expression of selected genes was validated by immunofluorescence on retinal wholemounts and cryosections and by flow cytometry. RESULTS Retinal endothelial cell sorting in wild type C57BL/6 mice was validated by comparative transcriptome analysis with retinal endothelial cells sorted from Tie2-GFP mice, which express GFP under the control of the endothelial-specific receptor tyrosine kinase promoter Tie2. RNA-Seq analysis of total retinal cells mainly brought to light upregulation of genes involved in antigen presentation and T cell activation during EAU. Specific transcriptome analysis of retinal endothelial cells allowed us to identify 82 genes modulated in retinal endothelial cells during EAU development. Protein expression of 5 of those genes (serpina3n, lcn2, ackr1, lrg1 and lamc3) was validated at the level of inner BRB cells. CONCLUSION Those data not only confirm the involvement of known pathogenic molecules but further provide a list of new candidate genes and pathways possibly implicated in inner BRB breakdown during non-infectious posterior uveitis.BACKGROUND Adolescent girls in Zambia face risks and vulnerabilities that challenge their healthy development into young women early marriage and childbearing, sexual and gender-based violence, unintended pregnancy and HIV. The Adolescent Girls Empowerment Program (AGEP) was designed to address these challenges by building girls’ social, health and economic assets in the short term and improving sexual behavior, early marriage, pregnancy and education in the longer term. The two-year intervention included weekly, mentor-led, girls group meetings on health, life skills and financial education. Additional intervention components included a health voucher redeemable for general wellness and reproductive health services and an adolescent-friendly savings account. METHODS A cluster-randomized-controlled trial with longitudinal observations evaluated the impact of AGEP on key indicators immediately and two years after program end. Baseline data were collected from never-married adolescent girls in 120 intervention clusters (3515 girls) and 40 control clusters (1146 girls) and again two and four years later.