Less is more: the “Safety Net Approach” balances precision and safety
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Deep learning-based image analysis in muscle histopathology using photo-realistic synthetic data
Artificial intelligence (AI), specifically Deep learning (DL), has revolutionized biomedical image analysis, but its efficacy is limited by the need for representative, high-quality large datasets with manual annotations. While latest research on synthetic data using AI-based generative models has shown promising results to tackle this problem, several challenges such as lack of interpretability and need for vast amounts of real data remain. This study aims to introduce a new approach—SYNTA—for the generation of photo-realistic synthetic biomedical image data to address the challenges associated with state-of-the art generative models and DL-based image analysis.
The impact of solar elevation angle on the net radiative effect of tropical cyclone clouds
In this study solar elevation angle is shown to have a dominant impact on the net radiation due to tropical cyclone (TC) clouds. As solar elevation angle increases, net cooling effects from TC clouds dominate over net warming effects. From 2001 to 2020, the radiative effect of TC clouds remained stable. However, because of the strong dependency on solar elevation angle, future changes in seasonal occurrence could affect this contribution.
Biodiversity offsets, their effectiveness and their role in a nature positive future
Biodiversity offsetting is a mechanism for addressing the impacts of development projects on biodiversity, but the practice remains controversial and its effectiveness generally poor. In the context of the Global Biodiversity Framework and the emergence of new approaches for mitigating damage, we need to learn from the past. In this Review, we explore biodiversity offsetting, its effectiveness and its future prospects, especially in relation to ‘nature positive’ goals. Offsets often fall short of their stated goal: to achieve at least no net loss of affected biodiversity. However, such failures are prominent because offsets have more explicit quantitative objectives than most other conservation approaches, whose effectiveness is also variable. These clear objectives provide the potential for the transparency that alternative approaches to addressing negative human impacts on biodiversity lack. Unfortunately, promising alternatives are scarce, so offsetting and offset-like mechanisms remain a necessary component of strategies to halt and reverse nature loss. However, improving their performance is essential. No quick and easy solution exists; instead, upholding best practice principles and rigorous implementation — including in the face of challenges from opposing narratives and interest groups — remains key.
Diversity of biomass usage pathways to achieve emissions targets in the European energy system
Biomass is a versatile renewable energy source with applications across the energy system, but it is a limited resource and its usage needs prioritization. We use a sector-coupled European energy system model to explore near-optimal solutions for achieving emissions targets. We find that provision of biogenic carbon has higher value than bioenergy provision. Energy system costs increase by 20% if biomass is excluded at a net-negative (−110%) emissions target and by 14% at a net-zero target. Dispatchable bioelectricity covering ~1% of total electricity generation strengthens supply reliability. Otherwise, it is not crucial in which sector biomass is used, if combined with carbon capture to enable negative emissions and feedstock for e-fuel production. A shortage of renewable electricity or hydrogen supply primarily increases the value of using biomass for fuel production. Results are sensitive to upstream emissions of biomass, carbon sequestration capacity and costs of direct air capture.
Pharmacodynamics of interspecies interactions in polymicrobial infections
The pharmacodynamic response of bacterial pathogens to antibiotics can be influenced by interactions with other bacterial species in polymicrobial infections (PMIs). Understanding the complex eco-evolutionary dynamics of PMIs and their impact on antimicrobial treatment response represents a step towards developing improved treatment strategies for PMIs. Here, we investigated how interspecies interactions in a multi-species bacterial community affect the pharmacodynamic response to antimicrobial treatment. To this end, we developed an in silico model which combined agent-based modeling with ordinary differential equations. Our analyses suggest that both interspecies interactions, modifying either drug sensitivity or bacterial growth rate, and drug-specific pharmacological properties drive the bacterial pharmacodynamic response. Furthermore, lifestyle of the bacterial population and the range of interactions can influence the impact of species interactions. In conclusion, this study provides a foundation for the design of antimicrobial treatment strategies for PMIs which leverage the effects of interspecies interactions.
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