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Nucleophosmin supports WNT-driven hyperproliferation and tumor initiation
No full textNucleophosmin (NPM1), a nucleolar protein frequently mutated in hematopoietic malignancies, is overexpressed in several solid tumors with poorly understood functional roles. Here, we demonstrate that Npm1 is upregulated after APC loss in WNT-responsive tissues and supports WNT-driven intestinal and liver tumorigenesis. Mechanistically, NPM1 loss induces ribosome pausing and accumulation at the 5'-end of coding sequences, triggering a protein synthesis stress response and p53 activation, which mediate this antitumorigenic effect. Collectively, our data identify NPM1 as a critical WNT effector that sustains WNT-driven hyperproliferation and tumorigenesis by attenuating the integrated stress response and p53 activation. Notably, NPM1 expression correlates with elevated WNT signaling and proliferation in human colorectal cancer (CRC), while CRCs harboring NPM1 deletions exhibit preferential TP53 inactivation, underscoring the clinical relevance of our findings. Being dispensable for adult epithelial homeostasis, NPM1 represents a promising therapeutic target in p53-proficient WNT-driven tumors, including treatment-refractory KRAS-mutant CRC, and hepatic cancers
Detection of disk-jet coprecession in a tidal disruption event
No full textTheories and simulations predict that intense space-time curvature near black holes bends the trajectories of light and matter, driving disk and jet precession under relativistic torques. However, direct observational evidence of disk-jet coprecession remains elusive. Here, we report the most compelling case to date: a tidal disruption event (TDE) exhibiting unprecedented 19.6-day quasi-periodic variations in both x-rays and radio, with x-ray amplitudes exceeding an order of magnitude. The nearly synchronized x-ray and radio variations suggest a shared mechanism regulating the emission regions. We demonstrate that a disk-jet Lense-Thirring precession model successfully reproduces these variations while requiring a low-spin black hole. This study uncovers previously uncharted short-term radio variability in TDEs, highlights the transformative potential of high-cadence radio monitoring, and offers profound insights into disk-jet physics
Defining clean Australian hydrogen beyond the hydrogen rainbow 2024 (in Tall Poppy Policy Briefs)
No full textSafety and efficacy of inhaled PEG-ADM in ARDS patients: a randomised controlled trial
No full textBackgroundThis study aimed to evaluate the safety and efficacy of inhaled pegylated adrenomedullin (PEG-ADM) for the management of acute respiratory distress syndrome in critically ill patients on mechanical ventilation.MethodsA Phase 2a/b randomised, double-blind, placebo-controlled multicentre trial was conducted. Patients with acute respiratory distress syndrome were assigned to receive PEG-ADM 960 μg or 1920 μg, or placebo. The primary endpoints were safety, efficacy, and ventilator-free survival at Day 28. Efficacy was assessed using ventilator-free survival and the clinical utility index, a composite endpoint that includes extravascular lung water index, oxygenation index, non-pulmonary Sequential Organ Failure Assessment score.ResultsNinety patients were randomised (PEG-ADM 960 μg: n = 29; PEG-ADM 1920 μg: n = 30; placebo: n = 31). Both dosages of PEG-ADM were well tolerated, with adverse event profiles similar to placebo. However, no significant efficacy was observed on the clinical utility index. Ventilator-free survival at Day 28 was lower in the PEG-ADM 960 μg group (52%) compared with the PEG-ADM 1920 μg (67%) and placebo (65%) groups. No significant differences were noted in overall mortality or the need for continued ventilation at Days 28 and 60.ConclusionInhaled PEG-ADM was well tolerated in patients with acute respiratory distress syndrome, but it did not improve clinical outcomes, which led to the early discontinuation after the first part of the trial for futility.Trial registrationClinicalTrials.gov: NCT04417036 (date of registration: 4 June 2020)
Use of inhaled corticosteroids in bronchiectasis: data from the European Bronchiectasis Registry (EMBARC)
No full textIntroduction: Current bronchiectasis guidelines advise against the use of inhaled corticosteroids (ICS) except in patients with associated asthma, allergic bronchopulmonary aspergillosis (ABPA) and/or chronic obstructive pulmonary disease (COPD). This study aimed to describe the use of ICS in patients with bronchiectasis across Europe. Methods: Patients with bronchiectasis were enrolled into the European Bronchiectasis Registry from 2015 to 2022. Patients were grouped into ICS users and non-users at baseline and clinical characteristics associated with ICS use were investigated. Patients were followed up for clinical outcomes of exacerbation, hospitalisation and mortality for up to 5 years. We evaluated if elevated blood eosinophil counts (above the laboratory upper limit of normal) modified the effect of ICS on exacerbations. Results: 19 324 patients were included for analysis and 10 109 (52.3%) were recorded as being prescribed ICS at baseline. After exclusion of patients with a history of asthma, COPD and/or ABPA, 3174/9715 (32.7%) patients with bronchiectasis were prescribed ICS. Frequency of ICS use varied across countries, ranging from 17% to 85% of included patients. ICS users had more severe disease, with significantly worse lung function, higher Bronchiectasis Severity Index scores and more frequent exacerbations at baseline (
Artificial intelligence-driven metabolomics of retinal nerve fibre layer to profile risks of mortality and cardiometabolic diseases
No full textRetinal nerve fibre layer (RNFL) is a non-invasive structural biomarker of cardiometabolic health, yet its biological underpinnings remain unknown. Here, we integrate advanced retinal optical biopsy and artificial intelligence (AI) algorithms with two complementary metabolomic assays across ethnically diverse cohorts to elucidate the metabolic basis underlying RNFL degeneration and its link to cardiometabolic disease (CMD) in Western cohort and Eastern cohort (Guangzhou Diabetic Eye Study, GDES). We identify 26 metabolic biomarkers significantly associated with RNFL thickness, most of which (ranging from 19 to 26) are linked to HDL composition and lipid transport, mediating a substantial proportion of the RNFL-CMD association (e.g., 63.7% for type 2 diabetes and 44.7% for myocardial infarction). AI-driven RNFL metabolic state model stratifies CMD risk with up to 21.8-fold enrichment between risk deciles and augments prediction while translating into clinical utility across genetic and demographic strata, particularly within socially vulnerable populations. This integrated approach highlights RNFL metabolic states as a shared basis underlying retinal-cardiometabolic connections and as early indicators that inform equitable CMD management
Correction to: ‘The need for joined-up thinking in critical raw materials research’ (2023) by Stephenson et al
No full textMixture of experts for decentralized generative AI and reinforcement learning in wireless networks: a comprehensive survey
No full textMixture of Experts (MoE) has emerged as a promising paradigm for scaling model capacity while preserving computational efficiency, particularly in large-scale machine learning architectures such as large language models (LLMs). Recent advances in MoE have facilitated its adoption in wireless networks to address the increasing complexity and heterogeneity of modern communication systems. This paper presents a comprehensive survey of the MoE framework in wireless networks, highlighting its potential in optimizing resource efficiency, improving scalability, and enhancing adaptability across diverse network tasks. We first introduce the fundamental concepts of MoE, including various gating mechanisms and the integration with generative AI (GenAI) and reinforcement learning (RL). Subsequently, we discuss the extensive applications of MoE across critical wireless communication scenarios, such as vehicular networks, unmanned aerial vehicles (UAVs), satellite communications, heterogeneous networks, integrated sensing and communication (ISAC), and mobile edge networks. Furthermore, key applications in channel prediction, physical layer signal processing, radio resource management, network optimization, and security are thoroughly examined. Additionally, we present a detailed overview of open-source datasets that are widely used in MoE-based models to support diverse machine learning tasks. Finally, this survey identifies crucial future research directions for MoE, emphasizing the importance of advanced training techniques, resource-aware gating strategies, and deeper integration with emerging 6G technologies
Work-life boundaries of health and social care workers: learning, reframing and resisting in crises
No full textThe COVID-19 pandemic profoundly disrupted work-life boundaries, particularly for health and social care (HSC) workers. This study explores the interplay between job demands, resources, and outcomes, using a sociologically informed perspective of the Job Demands-Resources (JD-R) model to examine how workers navigated boundary challenges during a prolonged crisis. Qualitative data were collected across three phases of research between 2021 and 2022, involving surveys and focus groups with 6,216 HSC workers from diverse roles and settings across the UK. The findings reveal dynamic shifts in work-life priorities, with risk management dominating early phases, followed by spatial, temporal, and cognitive boundary challenges. Relational resources, including managerial and family support, and individual strategies, such as self-care, reframing, and resilience, were critical in mitigating stress. However, inconsistent organizational support exacerbated burnout, career transitions, and service delivery challenges. This study extends JD-R theory by incorporating work-life boundaries as both a resource and a site of resistance, highlighting the nuanced ways organizational structures, relational dynamics, and individual agency shape boundary management. These findings contribute to understanding the sociological dimensions of boundary management and offer new theoretical and practical insights for navigating crises in high-demand sectors