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In the field of complex autoimmune diseases such as systemic lupus erythematosus (SLE), systems immunology approaches have proven invaluable in translational research settings. Large-scale datasets of transcriptome profiling have been collected and made available to the research community in public repositories, but remain poorly accessible and usable by mainstream researchers. Enabling tools and technologies facilitating investigators' interaction with large-scale datasets such as user-friendly web applications could promote data reuse and foster knowledge discovery. Microarray blood transcriptomic data from the LUPUCE cohort (publicly available on Gene Expression Omnibus, GSE49454), which comprised 157 samples from 62 adult SLE patients, were analyzed with the third-generation (BloodGen3) module repertoire framework, which comprises modules and module aggregates. These well-characterized samples corresponded to different levels of disease activity, different types of flares (including biopsy-proven lupus nephritis), different auto-antibody profiles and different levels of interferon signatures. A web application was deployed to present the aggregate-level, module-level and gene-level analysis results from LUPUCE dataset. Users can explore the similarities and heterogeneity of SLE samples, navigate through different levels of analysis, test hypotheses and generate custom fingerprint grids and heatmaps, which may be used in reports or manuscripts. This resource is available via this link: https://immunology-research.shinyapps.io/LUPUCE/. This web application can be employed as a stand-alone resource to explore changes in blood transcript profiles in SLE, and their relation to clinical and immunological parameters, to generate new research hypotheses.
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http://dx.doi.org/10.1093/database/baae045 | DOI Listing |
JMIR Res Protoc
September 2025
University of Nevada, Las Vegas, Las Vegas, NV, United States.
Background: In-hospital cardiac arrest (IHCA) remains a public health conundrum with high morbidity and mortality rates. While early identification of high-risk patients could enable preventive interventions and improve survival, evidence on the effectiveness of current prediction methods remains inconclusive. Limited research exists on patients' prearrest pathophysiological status and predictive and prognostic factors of IHCA, highlighting the need for a comprehensive synthesis of predictive methodologies.
View Article and Find Full Text PDFJMIR Hum Factors
September 2025
Media Psychology Lab, Department of Communication Science, KU Leuven, Leuven, Belgium.
Background: Out-of-hospital cardiac arrests (OHCAs) are a leading cause of death worldwide, yet first responder apps can significantly improve outcomes by mobilizing citizens to perform cardiopulmonary resuscitation before professional help arrives. Despite their importance, limited research has examined the psychological and behavioral factors that influence individuals' willingness to adopt these apps.
Objective: Given that first responder app use involves elements of both technology adoption and preventive health behavior, it is essential to examine this behavior from multiple theoretical perspectives.
J Med Internet Res
September 2025
Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Leipzig, Germany.
Background: The loss of a loved one is a common yet stressful event in later life. Internet- and mobile-based interventions have been proposed as an effective treatment approach for individuals with prolonged grief.
Objective: The AgE-health study aimed to investigate the efficacy of an eHealth intervention, trauer@ktiv, in reducing prolonged grief symptoms in a sample of older adults.
Appl Biochem Biotechnol
September 2025
School of Biological Sciences, University of the Punjab, Quaid-E-Azam Campus, P.O. 54590, Lahore, Pakistan.
Recombinant DNA technology is widely used to produce industrially and pharmaceutically important proteins. In silico analysis, performed before executing wet lab experiments has been greatly helpful in this connection. A shift in protein analysis has been observed over the past decade, driven by advancements in bioinformatics databases, tools, software, and web servers.
View Article and Find Full Text PDFInt J Comput Assist Radiol Surg
September 2025
Institute of Computer Science, Friedrich-Schiller-Universität, Fürstengraben 1, 07743, Jena, Thuringia, Germany.
Purpose: Cerebral aneurysms are blood-filled bulges that form at weak points in blood vessel walls, and their rupture can lead to life-threatening consequences. Given the high risk associated with these aneurysms, thorough examination and analysis are essential for determining appropriate treatment. While existing tools such as ANEULYSIS and its web-based counterpart WEBANEULYSIS provide interactive means for analyzing simulated aneurysm data, they lack support for collaborative analysis, which is crucial for enhancing interpretation and improving treatment decisions in medical team meetings.
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