Contactless and short-range vital signs detection with doppler radar millimetre-wave (76-81 GHz) sensing firmware.

Vital signs such as heart rate (HR) and respiration rate (RR) are essential physiological parameters that are routinely used to monitor human health and bodily functions. They can be continuously monitored through contact or contactless measurements performed in the home or a hospital. In this study, a contactless Doppler radar W-band sensing system was used for short-range, contactless vital sign estimation.

The role of urine metabolomics in the diagnosis and management of adult and pediatric Crohn's disease and ulcerative colitis.

Introduction: Urine metabolomics offers a non-invasive approach to diagnose and manage inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), by identifying distinct metabolic signatures.

Objectives: This narrative review summarizes current findings on urinary metabolites in IBD, evaluating their roles in disease differentiation, assessment of activity, and monitoring therapeutic response.

Methods: A comprehensive literature search of PubMed and MEDLINE up to October 2023 was conducted using keywords, such as 'urine metabolomics', 'inflammatory bowel disease', 'Crohn's disease', 'ulcerative colitis', and 'urinary biomarkers'.

A Needs-Based Assessment of Older Immigrants Experiencing Loneliness and Social Isolation and the Effectiveness of Interventions Responding to the Identified Needs: An Umbrella Review and Research Update.

This umbrella review and research update explores experiences of loneliness and social isolation in older immigrants to understand their support needs and the effectiveness of current interventions. Nine quantitative and qualitative studies discussing loneliness and/or social isolation in older immigrants were identified. Six key themes emerged: language and cultural barriers, life-course intersections, family relationships and obligations, meaningful opportunities as a counter-strategy, regaining self-esteem, and effectiveness of peer/community support.

Putting computational models of immunity to the test - an invited challenge to predict vaccination outcomes.

Systems vaccinology studies have been used to build computational models that predict individual vaccine responses and identify the factors contributing to differences in outcome. Comparing such models is challenging due to variability in study designs. To address this, we established a community resource to compare models predicting booster responses and generate experimental data for the explicit purpose of model evaluation.

Enhancing personalized gene expression prediction from DNA sequences using genomic foundation models.

Artificial intelligence (AI)/deep learning (DL) models that predict molecular phenotypes like gene expression directly from DNA sequences have recently emerged. While these models have proven effective at capturing the variation across genes, their ability to explain inter-individual differences has been limited. We hypothesize that the performance gap can be narrowed through the use of pre-trained embeddings from the Nucleotide Transformer, a large foundation model trained on 3,000+ genomes.