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Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use-such as the possible influence of recommendation on the evolution of systems that use it-and finally discuss open research directions and challenges.

The present study is a reasonable next step in a systematic assessment of how task demands and workload are related to performance in EMR-evolving environments.

Background Glucagon-like peptide-1 (GLP-1) and its based agents improve glycemic control. Although their attenuating effect on hepatic glucose output has drawn our attention for decades, the potential mechanisms remain unclear. Methods Cytokine array kit was used to assess cytokine profiles in db/db mice and mouse primary hepatocytes treated with exenatide (exendin-4). Two diabetic mouse models ( db/db and Pax6 m/+ ) were treated with a GLP-1 analog exenatide or liraglutide. The expression and secretion of fibroblast growth factor 21 (FGF21) in the livers of diabetic mice, primary mouse and human hepatocytes, and the human hepatic cell line HepG2 treated with or without GLP-1 analog were measured. Blockage of FGF21 with neutralizing antibody or siRNA, or hepatocytes isolated from Fgf21 knockout mice were used, and the expression and activity of key enzymes in gluconeogenesis were analyzed. Serum FGF21 level was evaluated in patients with type 2 diabetes (T2D) receiving exenatide treatment. Findings Utilizing the cytokine array, we identified that FGF21 secretion was upregulated by exenatide (exendin-4). Similarly, FGF21 production in hepatocytes was stimulated by exenatide or liraglutide. FGF21 blockage attenuated the inhibitory effects of the GLP-1 analogs on hepatic glucose output. Similar results were also observed in primary hepatocytes from Fgf21 knockout mice. Furthermore, exenatide treatment increased serum FGF21 level in patients with T2D, particularly in those with better glucose control. Interpretation We identify that function of GLP-1 in inhibiting hepatic glucose output is mediated via the liver hormone FGF21. Thus, we provide a new extra-pancreatic mechanism by which GLP-1 regulates glucose homeostasis. Fund National Key Research and Development Program of China, the National Natural Science Foundation of China, the Natural Science Foundation of Beijing and Peking University Medicine Seed Fund for Interdisciplinary Research.

Introduction: To enhance the performance evaluation of Clinical and Translational Science Award (CTSA) hubs, we examined the utility of advanced bibliometric measures that go beyond simple publication counts to demonstrate the impact of translational research output. Methods: The sampled data included North Carolina Translational and Clinical Science Institute (NC TraCS)-supported publications produced between September 2008 and March 2017. We adopted advanced bibliometric measures and a state-of-the-art bibliometric network analysis tool to assess research productivity, citation impact, the scope of research collaboration, and the clusters of research topics. Results: Totally, 754 NC TraCS-supported publications generated over 24,000 citation counts by April 2017 with an average of 33 cites per article. NC TraCS-supported research papers received more than twice as many cites per year as the average National Institute of Health-funded research publications from the same field and time. We identified the top productive researchers and their networks within the CTSA hub. Findings demonstrated the impact of NC TraCS in facilitating interdisciplinary collaborations within the CTSA hub and across the CTSA consortium and connecting researchers with right peers and organizations. Conclusion: Both improved bibliometrics measures and bibliometric network analysis can bring new perspectives to CTSA evaluation via citation influence and the scope of research collaborations.

Background Anxiety and depressive disorders are the most common mental health conditions among African American women. Despite the need for mental health care, African American women significantly underuse mental health services. Previous mobile health studies revealed significant improvements in anxiety or depressive symptoms after intervention. The use of mobile apps offers the potential to eliminate or mitigate barriers for African American women who are seeking access to mental health services and resources. Objective This study aims to evaluate the usability of the prototype of an app that is designed for supporting the self-management of anxiety and depression in African American women. Methods Individual usability testing sessions were conducted with 15 participants in Chapel Hill, North Carolina. Cognitive walkthrough and think-aloud protocols were used to evaluate the user interface. Eye-tracking glasses were used to record participants’ visual focus and gaze path as they performed the tasks. The Questionnaire for User Interface Satisfaction was administered after each session to assess the participants’ acceptance of the app. Results Participants rated the usability of the prototype positively and provided recommendations for improvement. The average of the mean scores for usability assessments (ie, overall reactions to the software, screen, terminology and app information, learning, and app capabilities) ranged from 7.2 to 8.8 on a scale of 0-9 (low to high rating) for user tasks. Most participants were able to complete each task with limited or no assistance. Design recommendations included improving the user interface by adding graphics and color, adding a tutorial for first-time users, curating a list of Black women therapists within the app, adding details about tracking anxiety and depression in the checkup graphs, informing users that they can use the talk-to-text feature for journal entries to reduce burden, relabeling the mental health information icon, monitoring for crisis support, and improving clickthrough sequencing. Conclusions This study provides a better understanding of user experience with an app tailored to support the management of anxiety and depression for African American women, which is an underserved group. As African American women have high rates of smartphone ownership, there is a great opportunity to use mobile technology to provide access to needed mental health services and resources. Future work will include incorporating feedback from usability testing and focus group sessions to refine and develop the app further. The updated app will undergo iterative usability testing before launching the pilot study to evaluate the feasibility and acceptability of the prototype.

The novel coronavirus disease (COVID-19) has caused a pandemic and global health crisis. Although normal operation and services in many libraries have been greatly disrupted, academic libraries in the United States were reportedly responding to challenges by pivoting to new ways to meet the users’ needs. This observational study was designed to investigate the status, services, and resources disclosed via websites of academic medical/health sciences libraries (MHSLs) in the United States and document how they adapted and continued to provide support to help fight the health crisis and the resulting “infodemic” through various means. A complete list of members was obtained from the website of the Association of Academic Health Sciences Libraries (AAHSL). The U.S.-based AAHSL member institutions were included in this study. Each American academic MHSL website and its associated webpages were browsed; web contents were categorized and analyzed based on four research questions proposed by this study. A descriptive analysis was conducted to summarize all findings. A total of 157 AAHSL member institutions were included in the study. These libraries spread all over the United States, and 90% of them announced closures of library buildings and facilities. A significant number of MHSLs quickly adapted to the evolving situation and transitioned their services and instruction to the online environment. The COVID-19 information sources adopted by MHSLs included the following ranked by frequency from high to low: The U.S. government agencies such as Centers for Disease Control and Prevention and National Library of Medicine, the World Health Organization, publishing communities, professional journals, organizations, local institutions, government agencies, and news channels. In addition, MHSLs undertook a series of actions to support academic communities and local healthcare professionals including resource curation, clinical care support, education, and outreach to the public. Through library guides, MHSLs provided comprehensive and customized search queries to help researchers locate the latest and relevant publications to COVID-19, curated multiple data resources and data exploration, and visualization tools, and selected the latest biomedical and health evidence in a wide range of topics. Other featured resources and services were associated with ethical issues (i.e., racism and prejudice), educational and entertainment information (e.g., virtual tours of parks), and personal experience documentation. This observational study is the most recent investigation and documentation on the status, services, and resources of the academic MHSLs in the United States during the initial U.S. outbreak of the COVID-19 pandemic. Although the current health crisis is taking a heavy toll on libraries nationwide, MHSLs are still managing to play a vital role in supporting the academic communities, healthcare facilities, and the general public and fighting against the pandemic and the resulting information crisis.

Objective Biomedical text summarization helps biomedical information seekers avoid information overload by reducing the length of a document while preserving the contents’ essence. Our systematic review investigates the most recent biomedical text summarization researches on biomedical literature and electronic health records by analyzing their techniques, areas of application, and evaluation methods. We identify gaps and propose potential directions for future research. Materials and Methods This review followed the PRISMA methodology and replicated the approaches adopted by the previous systematic review published on the same topic. We searched 4 databases (PubMed, ACM Digital Library, Scopus, and Web of Science) from January 1, 2013 to April 8, 2021. Two reviewers independently screened title, abstract, and full-text for all retrieved articles. The conflicts were resolved by the third reviewer. The data extraction of the included articles was in 5 dimensions: input, purpose, output, method, and evaluation. Results Fifty-eight out of 7235 retrieved articles met the inclusion criteria. Thirty-nine systems used single-document biomedical research literature as their input, 17 systems were explicitly designed for clinical support, 47 systems generated extractive summaries, and 53 systems adopted hybrid methods combining computational linguistics, machine learning, and statistical approaches. As for the assessment, 51 studies conducted an intrinsic evaluation using predefined metrics. Discussion and Conclusion This study found that current biomedical text summarization systems have achieved good performance using hybrid methods. Studies on electronic health records summarization have been increasing compared to a previous survey. However, the majority of the works still focus on summarizing literature.