SUMMARYOver the past decade, hundreds of studies have characterized the microbial communities found in human-associated built environments (BEs). These have focused primarily on how the design and use of our built spaces have shaped human-microbe interactions and how the differential selection of certain taxa or genetic traits has influenced health outcomes. It is now known that the more removed humans are from the natural environment, the greater the risk for the development of autoimmune and allergic diseases, and that indoor spaces can be harsh, selective environments that can increase the emergence of antimicrobial-resistant and virulent phenotypes in surface-bound communities. However, despite the abundance of research that now points to the importance of BEs in determining human-microbe interactions, only a fraction of non-human animal structures have been comparatively explored. It is here, in the context of human-associated BE research, that we consider the microbial ecology of animal-built natural nests and burrows, as well as artificial enclosures, and point to areas of primary interest for future research.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10732082PMC
http://dx.doi.org/10.1128/mmbr.00121-21DOI Listing

Publication Analysis

Top Keywords

built environment
8
human-associated built
8
human-microbe interactions
8
microbiology built
4
environment harnessing
4
harnessing human-associated
4
environment inform
4
inform study
4
study design
4
design animal
4

Similar Publications

Modernizing power systems into smart grids has introduced numerous benefits, including enhanced efficiency, reliability, and integration of renewable energy sources. However, this advancement has also increased vulnerability to cyber threats, particularly False Data Injection Attacks (FDIAs). Traditional Intrusion Detection Systems (IDS) often fall short in identifying sophisticated FDIAs due to their reliance on predefined rules and signatures.

View Article and Find Full Text PDF

The genetic basis of complex traits involves the function of many genes with small effects as well as complex gene-gene and gene-environment interactions. As one of the major players in complex diseases, the role of gene-environment interactions has been increasingly recognized. Motivated by epidemiology studies to evaluate the joint effect of environmental mixtures, we developed a functional varying-index coefficient model (FVICM) to assess the combined effect of environmental mixtures and their interactions with genes, under a longitudinal design with quantitative traits.

View Article and Find Full Text PDF

Antibody production is central to protection against new pathogens and cancers, as well as to certain forms of autoimmunity. Antibodies often originate in the lymph node (LN), specifically at the extrafollicular border of B cell follicles, where T and B lymphocytes physically interact to drive B cell maturation into antibody-secreting plasmablasts. In vitro models of this process are sorely needed to predict aspects of the human immune response.

View Article and Find Full Text PDF

Introduction: The transition to electric vehicles (EVs) has highlighted the need for efficient diagnostic methods to assess the state of health (SoH) of lithium-ion batteries (LIBs) at the end of their life cycle. Electrochemical Impedance Spectroscopy (EIS) offers a non-invasive technique for determining battery degradation. However, automating this process in industrial settings remains a challenge.

View Article and Find Full Text PDF

Prediction of induction motor faults using machine learning.

Heliyon

January 2025

Electrical and Information Engineering Department, Covenant University, P.M.B 1023, Ota, 112212, Ogun State, Nigeria.

Unplanned downtime in industrial sectors presents significant challenges, impacting both production efficiency and profitability. To tackle this issue, companies are actively working towards optimizing their operations and reducing disruptions that hinder their ability to meet customer demands and financial goals. Predictive maintenance, utilizing advanced technologies like data analytics, machine learning, and IoT devices, offers real-time equipment data monitoring and analysis.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!