Predictors of Morbidity and Mortality After Fall-related Traumatic Brain Injury.

Objective: The authors investigate predictors of morbidity and mortality in patients after fall-related Traumatic Brain Injury (TBI) in a retrospective cohort study of patients presenting to a single emergency department.

Methods: This study analyzed the predictors of a subset of patients who come to the emergency department (ED) of a Level 1 trauma center who sustained a TBI after a fall. The study also examines the utility of head Computed Tomography (CT) scan as a predictor in determining outcomes such as hospital admission, in-hospital death, and Intensive Care Unit (ICU) admission.

Invisible Scribes: Can Nurses Trust Ambient AI for Clinical Documentation?

Ambient artificial intelligence listening tools promise faster nursing documentation and improved patient engagement, yet they introduce risks of hallucinations, omission, and bias when nurses are excluded from the design and oversight process. Empowering nurses through continuing education and leadership in model development, deployment, and auditing is crucial for ensuring safe and equitable integration across care settings.

Lessons from the European Mpox Outbreak: Strengthening Cohort Research for Future Pandemic Preparedness.

Background: Well-designed cohort studies are crucial for pandemic preparedness informing evidence-based infection prevention and treatment strategies.

Objectives: Following the 2022 mpox outbreak in Europe, this scoping review critically evaluates the design, implementation, and characteristics of cohort studies focusing on mpox. The aim is to inform recommendations for the Cohort Coordination Board and CoMeCT to enhance cohort study research and improve preparedness.

From ageing clocks to human digital twins in personalising healthcare through biological age analysis.

Age is the most important risk factor for the majority human diseases, leading to the exploration of innovative approaches, including the development of predictors to estimate biological age (BA). These predictors offer promising insights into the ageing process and age-related diseases. With real-time, multi-modal data streams and continuous patient monitoring, these BA can also inform the construction of 'human digital twins', quantifying how age-related changes impact health trajectories.

Leveraging functional annotations to map rare variants associated with Alzheimer disease with gruyere.

Increased availability of whole-genome sequencing (WGS) has facilitated the study of rare variants (RVs) in complex diseases. Multiple RV association tests are available to study the relationship between genotype and phenotype, but most do not fully leverage the availability of variant-level functional annotations. We propose genome-wide rare variant enrichment evaluation (gruyere), an empirical Bayesian framework that complements existing methods by learning global, trait-specific weights for functional annotations to improve variant prioritization.

Upper endoscopy in Solomon Islands: A four-year retrospective study.

ObjectiveGastrointestinal diseases are common, yet some countries still lack endoscopy. Modern flexible endoscopy was introduced to the Solomon Islands National Referral Hospital (NRH) in 2012, but little is known about gastrointestinal disease in the country.MethodsThis retrospective cohort study describes trends in upper gastrointestinal diseases to inform local research and health programming.

Immunotherapy in Melanoma.

This chapter explores systemic treatment strategies for cutaneous melanoma across neoadjuvant, adjuvant, and Stage IV settings. Neoadjuvant therapy aims to reduce tumor burden pre-surgery, primarily using immune checkpoint inhibitors like nivolumab plus ipilimumab, showing promising response rates. Adjuvant therapy, post-resection, leverages immunotherapy (e.

Evaluating surrogates for overall survival in the adjuvant treatment of bladder cancer with chemotherapy.

Introduction: Surrogates for overall survival (OS) can expedite the development of adjuvant treatments for bladder cancer. We evaluated whether disease-free survival (DFS) or distant metastasis-free survival (DMFS) are valid surrogates for OS in patients with muscle-invasive disease treated with cisplatin-based chemotherapy after radical cystectomy.

Methods: We analyzed individual patient data from 1075 patients enrolled in 9 randomized controlled trials (RCTs) identified by systematic review.

Sleep, rest-activity rhythms, and the Charlson Comorbidity Index in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) and Sueño.

This study aimed to investigate the role of sleep and circadian health on disparities in overall disease burden among individuals of Hispanic/Latino heritage with differing nativity backgrounds. This study evaluated associations between self-reported sleep (from HCHS/SOL baseline, 2008-2011) and actigraphy-derived sleep/circadian measures (from Sueño, 2010-2013) with multimorbidity at follow-up (2011-2017). Zero-inflated Poisson regression modeled associations between categorical sleep metrics (e.

Functional brain network identification in opioid use disorder using machine learning analysis of resting-state fMRI BOLD signals.

Understanding the neurobiology of opioid use disorder (OUD) using resting-state functional magnetic resonance imaging (rs-fMRI) may help inform treatment strategies to improve patient outcomes. Recent literature suggests time-frequency characteristics of rs-fMRI blood oxygenation level-dependent (BOLD) signals may offer complementary information to traditional analysis techniques. However, existing studies of OUD analyze BOLD signals using measures computed across all time points.

Advancing AI initiatives in nursing academics: Case studies and insights from thought leaders.

Artificial Intelligence (AI) is transforming the landscape of health care and nursing research and education. As key stakeholders in this transformation, nursing faculty are crucial in driving strategic and operational AI initiatives to develop appropriate competence within the workforce to ensure the safe application of these technologies in nursing and care. To discuss the ways nursing faculty can be actively involved in AI initiatives, a panel was convened at the Third International Workshop on Artificial Intelligence in Nursing (AINurse24).

Multi-organ AI Endophenotypes Chart the Heterogeneity of Pan-disease in the Brain, Eye, and Heart.

Disease heterogeneity and commonality pose significant challenges to precision medicine, as traditional approaches frequently focus on single disease entities and overlook shared mechanisms across conditions. Inspired by pan-cancer and multi-organ research, we introduce the concept of "pan-disease" to investigate the heterogeneity and shared etiology in brain, eye, and heart diseases. Leveraging individual-level data from 129,340 participants, as well as summary-level data from the MULTI consortium, we applied a weakly-supervised deep learning model (Surreal-GAN) to multi-organ imaging, genetic, proteomic, and RNA-seq data, identifying 11 AI-derived biomarkers - called Multi-organ AI Endophenotypes (MAEs) - for the brain (Brain 1-6), eye (Eye 1-3), and heart (Heart 1-2), respectively.

Sleep chart of biological aging clocks across organs and omics.

Optimal sleep plays a vital role in promoting healthy aging and enhancing longevity. This study proposes a Sleep Chart to assess the relationship between sleep duration and 23 biological aging clocks across 17 organ systems or tissues and 3 omics data types (imaging, proteomics, and metabolomics). First, a systemic, U-shaped pattern shows that both short (<6 hours) and long (>8 hours) sleep duration are linked to elevated biological age gaps (BAGs) across 9 brain and body systems and 3 omics types, with optimal sleep time varying by organ and sex ([6.

Tau-Driven Coordination of Microtubule-Actin Crosstalk in Cell-Sized Vesicles.

The coordination of microtubules (MTs) and actin filaments is essential for cytoskeletal organization, yet the factors that affect their integration remain unclear. Here, we reconstitute cytoskeletal networks in giant unilamellar vesicles to characterize MT-actin crosstalk mediated by tau, a microtubule-associated protein. We show that tau promotes the organization of MTs into diverse architectures, including bundles, clusters, and networks, depending on its concentration and vesicle size.

Dietary attribution to burden of chronic disease in Australia: a systematic analysis of the Australian Institute of health and welfare 2024 national burden of disease dataset.

Background: Non-communicable chronic diseases (NCDs), including cardiovascular diseases, cancer, chronic kidney disease (CKD), and type 2 diabetes mellitus (T2DM), pose a significant burden on Australia's healthcare system. Despite advancements in disease prevention and management, NCDs remain the leading cause of morbidity and mortality. This study aimed to assess trends in the burden of NCDs and the impact of dietary risks in Australia from 2003 to 2024 using data from the Australian Institute of Health and Welfare (AIHW).

An extension of the Benefit Risk Assessment of VaccinEs toolkit to evaluate Comirnaty and Spikevax vaccination in the European Union.

Amid the global COVID-19 pandemic, vaccines were conditionally authorized for human use to protect against severe infection. The Benefit Risk Assessment of VaccinEs (BRAVE) toolkit, a user-friendly R Shiny application, was developed retrospectively together with the European Medicine Agency (EMA) with the aim of fulfilling the need for flexible tools to assess vaccine benefits and risks during and outside a pandemic situation. This study employed BRAVE to evaluate the impact of COVID-19 mRNA vaccines across 30 European Union (EU)/EEA countries by quantifying the number of prevented clinical events [i.

Cyanobacteria Join the Kahalalide Conversation: Genome and Metabolite Evidence for Structurally Related Peptides.

Kahalalide F is a cyclic depsipeptide with notable anticancer properties, initially discovered from the green alga sp. and its molluscan predator . Recent studies have pinpointed a bacterial endosymbiont of the green alga, Endobryopsis kahalalidefaciens, as the true producer of kahalalide F.

Advances in artificial intelligence and precision nutrition approaches to improve maternal and child health in low resource settings.

Malnutrition continues to be a major threat to health, particularly maternal and child health in low resource settings, resulting in impairments in cognitive function, growth, and development, and metabolic diseases later in life. Nutritional assessment is a cornerstone of any successful nutrition intervention or program whether in the community or at the clinic. Improved computational power and advances in technology may enable precision nutrition-based approaches for maternal and child health, which can complement current methods for nutritional assessment to identify clinical, biochemical, microbiome-related, social, and environmental characteristics to predict responses to nutritional interventions or programs.

Engineered Microbial-Based Therapeutics Nose No Bounds: Extending Innovation to Rhinologic Disease Management.

Advancements in synthetic biology provide an opportunity to deliver targeted and controllable precision therapy to address sinonasal diseases. By leveraging the natural microbial ecosystem of the nasal mucosa and its mutability, engineered therapeutic bacteria present a promising treatment modality currently underexplored in this field. Investigating the practical application of this emerging therapeutic option stands to enhance our management of rhinologic diseases.

Towards cardiac MRI foundation models: Comprehensive visual-tabular representations for whole-heart assessment and beyond.

Cardiac magnetic resonance (CMR) imaging is the gold standard for non-invasive cardiac assessment, offering rich spatio-temporal views of the heart's anatomy and physiology. Patient-level health factors, such as demographics, metabolic, and lifestyle, are known to substantially influence cardiovascular health and disease risk, yet remain uncaptured by CMR alone. To holistically understand cardiac health and to enable the best possible interpretation of an individual's disease risk, CMR and patient-level factors must be jointly exploited within an integrated framework.