143174 research outputs found
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Soybean Rhizosphere Microbial Communities for Enhancing Yield and Biomass Under Drought Stress
No full textImperial Users onl
Investigating Within-Host Selection in SARS-CoV-2 Using a Wright-Fisher Time-Series Model
No full textImperial Users onl
Sharing emissions and removals for meeting the Paris Agreement through a distributive and corrective justice lens
No full textCarbon dioxide removal (CDR) is critical for achieving net-zero and net-negative CO2 emissions that can halt and potentially reverse global warming, respectively. However, reliable CDR is still costly and comes with considerable technological and ecological uncertainties. Despite the centrality of equity in the Paris Agreement, no integrated framework exists to equitably allocate responsibilities for CDR and residual emissions among countries. Here, we present a justice-based framework that separates out ethical considerations for equitably allocating gross emissions and gross CDR, addressing how these contributions shift before and after reaching global net-zero CO2 emissions. The framework distinguishes between CDR delivered as a common good to reach a collective global climate outcome, and CDR that is used to pay off carbon debts due to emissions overconsumption. We offer a new perspective for how nations with substantial historical responsibilities and emerging economies with increasing capacities can collaborate and equitably share the CDR burden, enhancing both international cooperation and national-level climate action
Catalysing Artificial Intelligence for Paediatric Tuberculosis Research (CAPTURE): protocol for establishing a global multicentre study establishing paediatric chest X-ray repository to evaluate computer-aided detection algorithms
No full textIntroduction
The substantial case detection gap in the field of child tuberculosis (TB) disease is largely driven by inadequate diagnostic tools and approaches. Chest radiographs (CXR) remain a key component in the evaluation of children and young adolescents (0-15 years) with presumptive TB, aiding clinicians in making the diagnosis and discriminating children with TB from those with other diseases. Widespread use and optimal interpretation of CXR is hampered by a lack of access to well-trained specialists to interpret images. Artificial intelligence CXR interpretation software, termed computer aided detection (CAD), are now well developed for adults, yet few products have been evaluated in children. The CXR features of child TB are different from those of adults, and as a result the performance of these CAD algorithms, largely developed for use in adults, will be sub-optimal when used in children. Adapting, or fine-tuning adult CAD algorithms, using CXR images from children with presumptive TB, could allow optimisation of these products for use in children. We therefore set out to develop a large image and data repository collected from children evaluated for TB (called Catalysing Artificial intelligence for Paediatric Tuberculosis Research, CAPTURE) with the purpose of evaluating current CAD products and then working with developers and other partners to optimize CAD algorithms for use in children.
Methods and analysis
We identified approximately 20 studies, from which potentially up to 11,000 CXRs could be utilized for the proposed project. CXRs and data were eligible for inclusion in the CAPTURE repository if collected from high quality child TB diagnostic studies that enrolled children with presumptive TB and if CXRs were obtained as part of the baseline assessment. All lead investigators of these studies are members of the CAPTURE consortium. The images and meta-data contributed are centrally collated and the key variable of TB case classification as Confirmed, Unconfirmed or Unlikely TB, using an established consensus case definition, are available. All CXRs included in the CAPTURE repository have a consensus radiological interpretation allocated by a panel of independent expert child TB CXR readers who have classified them as ‘unreadable’, ‘normal’, ‘abnormal typical of TB’ or ‘abnormal not typical of TB’. To determine diagnostic performance of existing CAD products, we will evaluate these against a primary composite clinical reference standard (Confirmed TB and Unconfirmed TB vs. Unlikely TB), as well as other secondary microbiological and radiological reference standards. A sub-set of images will be subsequently allocated to a ‘training set’ and made available to developers, academic groups or other parties to either develop novel paediatric CAD products or fine-tune existing adult ones, which will then be re-evaluated by the CAPTURE team using an image sub-set (‘validation set’) that is independent of the training set.
Ethics and dissemination
The CAPTURE study has been approved by Stellenbosch University Health Research Ethics Committee (N22/09/113), with additional ethics approval or waivers by relevant local authorities obtained by consortium members contributing data if required. The final pooled, harmonized and cleaned dataset, as well as the de-identified, renamed CXR images are stored on a secure cloud-based server. All analyses of existing CAD products, as well as the paediatric-optimised products, will be published in peer-reviewed publications and shared with other stakeholders like the World Health Organization and donor and procurement organizations to guide policy updates and procurement pathways to ensure widespread uptake
A multi-modal vision knowledge graph of cardiovascular disease
No full textUnderstanding gene-disease associations is important for uncovering pathological mechanisms and identifying potential therapeutic targets. Knowledge graphs can represent and integrate data from multiple
biomedical sources, but lack individual-level information on target organ structure and function. Here we
develop CardioKG, a knowledge graph that integrates over 200,000 computer vision-derived cardiovascular phenotypes from biomedical images with data extracted from 18 biological databases to model over
a million relationships. We used a variational graph auto-encoder to generate node embeddings from the
knowledge graph to predict gene-disease associations, assess druggability and identify drug repurposing strategies. The model predicted genetic associations and therapeutic opportunities for leading causes
of cardiovascular disease, which were associated with improved survival. Candidate therapies included
methotrexate for heart failure and gliptins for atrial fibrillation, and the addition of imaging data enhanced
pathway discovery. These capabilities support the use of biomedical imaging to enhance graph-structured
models for identifying treatable disease mechanisms
How does the history of human land-use influence ecological community shifts?
No full textImperial Users onl
Systematic identification of bacterial factors driving Staphylococcus aureus intracellular lifestyle in non-professional phagocytes
No full textStaphylococcus aureus is a major human pathogen responsible for severe infections. While traditionally described as extracellular, increasing evidence establishes S. aureus as a facultative intracellular pathogen. Intracellularity contributes to immune evasion, dissemination, and antibiotic failure. To identify bacterial factors critical for S. aureus invasion, intracellular replication, persistence, and host cytotoxicity, we screened a comprehensive collection of 1,920 S. aureus mutants (Nebraska transposon mutant library) in epithelial cells across five timepoints (0.5 to 48 hours post-infection). We identified 73 bacterial factors strongly modulating S. aureus intracellularity, including mutants displaying multiple phenotypes. Most of these factors have not been linked to intracellular lifestyle. Among these, we characterized the nicotinamidase PncA as a novel regulator of the agr system via redox state modulation, strongly impacting virulence. This study provides a systematic analysis of S. aureus factors critical for intracellular lifestyle, with implications for the development of antimicrobial strategies targeting this resilient bacterial population
