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Translating the ever-increasing wealth of information on microbiomes (environment, host or built environment) to advance our understanding of system-level processes is proving to be an exceptional research challenge. One reason for this challenge is that relationships between characteristics of microbiomes and the system-level processes that they influence are often evaluated in the absence of a robust conceptual framework and reported without elucidating the underlying causal mechanisms. The reliance on correlative approaches limits the potential to expand the inference of a single relationship to additional systems and advance the field. We propose that research focused on how microbiomes influence the systems they inhabit should work within a common framework and target known microbial processes that contribute to the system-level processes of interest. Here, we identify three distinct categories of microbiome characteristics (microbial processes, microbial community properties and microbial membership) and propose a framework to empirically link each of these categories to each other and the broader system-level processes that they affect. We posit that it is particularly important to distinguish microbial community properties that can be predicted using constituent taxa (community-aggregated traits) from those properties that cannot currently be predicted using constituent taxa (emergent properties). Existing methods in microbial ecology can be applied to more explicitly elucidate properties within each of these three categories of microbial characteristics and connect them with each other. We view this proposed framework, gleaned from a breadth of research on environmental microbiomes and ecosystem processes, as a promising pathway with the potential to advance discovery and understanding across a broad range of microbiome science.
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http://dx.doi.org/10.1038/s41564-018-0201-z | DOI Listing |
Arch Toxicol
September 2025
Norwegian Scientific Committee for Food and Environment, Norwegian Institute of Public Health, Oslo, Norway.
The transition from traditional animal-based approaches and assessments to New Approach Methodologies (NAMs) marks a scientific revolution in regulatory toxicology, with the potential of enhancing human and environmental protection. However, implementing the effective use of NAMs in regulatory toxicology has proven to be challenging, and so far, efforts to facilitate this change frequently focus on singular technical, psychological or economic inhibitors. This article takes a system-thinking approach to these challenges, a holistic framework for describing interactive relationships between the components of a system of interest.
View Article and Find Full Text PDFAsia Pac J Oncol Nurs
December 2025
Red Cross College of Nursing, Chung-Ang University, Seoul, Republic of Korea.
Objective: The lack of a clear and unified definition of shared decision-making (SDM) may hinder its effective application in oncology care. This study aims to clarify the concept of SDM specifically in the context of early-stage breast cancer treatment through an evolutionary concept analysis.
Methods: A systematic search was conducted across PubMed, CINAHL, PsycINFO, Cochrane, and EMBASE databases for articles published from January 2015 to December 2024.
Adv Nutr
September 2025
Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, 715 Sumter Street, CLS 513C, SC 29208, USA.
Human activities contribute to large shifts in the global climate, with far-reaching impacts on ecosystems, societies, and human health. Modern food systems-designed to produce convenience foods that tend to have high inflammatory potential-exacerbate environmental degradation and shape the interwoven challenges of climate, nutrition, and health. Over the past three decades, extreme weather has worsened and poor diets have led to more inflammation-related health problems-two parallel trends that are exposing system-wide weaknesses and harming global health.
View Article and Find Full Text PDFJMIR Form Res
September 2025
Department of Psychiatry, Cambridge Health Alliance, Cambridge, MA, United States.
Background: Measurement-based care (MBC), including remote MBC, is increasingly being considered or implemented for mental health treatment and outcomes monitoring in routine clinical care. However, little is known about the health equity implications in real-world practice or the impact on patient-provider relationships in lower-resource systems that offer mental health treatment for diverse patients.
Objective: This hypothesis-generating study examined the drivers of MBC implementation outcomes, the implications for health equity, and the impact of MBC on therapeutic alliance (TA).
We envision the Full-Body AI Agent as a comprehensive AI system designed to simulate, analyze, and optimize the dynamic processes of the human body across multiple biological levels. By integrating computational models, machine learning tools, and experimental platforms, this system aims to replicate and predict both physiological and pathological processes, ranging from molecules and cells to tissues, organs, and entire body systems. Central to the Full-Body AI Agent is its emphasis on integration and coordination across these biological levels, enabling analysis of how molecular changes influence cellular behaviors, tissue responses, organ function, and systemic outcomes.
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