A bacterium first seen in space is now infecting humans
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Aerospace medicine in China: advancements and perspectives
With the rapid growth of China’s space industry, long-term manned space missions face challenges from the complex space environment, posing risks to human health. Aerospace medicine, a key field, addresses these risks by researching the impacts of space on biochemical changes, cognitive abilities, and immune systems. This article reviews China’s aerospace medicine research, summarizing efforts from various institutions and offering insights for future developments in the field.
Conceptualizing space environmental sustainability
Recent advancements have significantly enhanced the capabilities for in-space servicing, assembly, and manufacturing (ISAM), to develop infrastructure in orbit and on the surface of celestial bodies. This progress is a departure from the traditional sustainability paradigm focused solely on Earth, highlighting the urgent need to define and operationalize the concept of “space sustainability” along with the development of an evaluation framework. The expansion of human activity into space, particularly in low-earth orbit, cis-lunar space, and beyond, underscores the critical importance of considering sustainability implications. Leveraging space resources offers economic growth and sustainable development opportunities, while reducing pressure on Earth’s ecosystems. This paradigm shift requires responsible and ethical utilization of space resources. A space sustainability assessment framework is essential for guiding ISAM capabilities, operations, missions, standards, and policies. This paper introduces an initial framework encompassing (1) pollution, (2) resource depletion, (3) landscape alteration, and (4) space environmental justice, with potential metrics (resources use and emissions, midpoint, and endpoint indicators) to measure impacts in the four domains.
The utility of animal models to inform the next generation of human space exploration
Animals have played a vital role in every stage of space exploration, from early sub-orbital flights to contemporary missions. New physiological and psychological challenges arise with plans to venture deeper into the solar system. Advances in chimeric and knockout animal models, along with genetic modification techniques have enhanced our ability to study the effects of microgravity in greater detail. However, increased investment in the purposeful design of habitats and payloads, as well as in AI-enhanced behavioral monitoring in orbit can better support the ethical and effective use of animals in deep space research.
Self-reports map the landscape of task states derived from brain imaging
Psychological states influence our happiness and productivity; however, estimates of their impact have historically been assumed to be limited by the accuracy with which introspection can quantify them. Over the last two decades, studies have shown that introspective descriptions of psychological states correlate with objective indicators of cognition, including task performance and metrics of brain function, using techniques like functional magnetic resonance imaging (fMRI). Such evidence suggests it may be possible to quantify the mapping between self-reports of experience and objective representations of those states (e.g., those inferred from measures of brain activity). Here, we used machine learning to show that self-reported descriptions of experiences across tasks can reliably map the objective landscape of task states derived from brain activity. In our study, 194 participants provided descriptions of their psychological states while performing tasks for which the contribution of different brain systems was available from prior fMRI studies. We used machine learning to combine these reports with descriptions of brain function to form a ‘state-space’ that reliably predicted patterns of brain activity based solely on unseen descriptions of experience (N = 101). Our study demonstrates that introspective reports can share information with the objective task landscape inferred from brain activity.
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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