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61,005 resultsShowing papers similar to Machine learning to predict dynamic changes of pathogenic Vibrio spp. abundance on microplastics in marine environment
ClearVibrio Colonization Is Highly Dynamic in Early Microplastic-Associated Biofilms as Well as on Field-Collected Microplastics
Researchers found that Vibrio colonization on polyethylene and polystyrene microplastics is highly dynamic during the first 10 hours of biofilm formation, with Vibrio abundance and species composition varying irregularly both in laboratory incubations and on field-collected Baltic Sea microplastics, complicating assessments of microplastics as vectors for pathogenic bacteria.
Dangerous hitchhikers? Evidence for potentially pathogenic Vibrio spp. on microplastic particles
Researchers tested whether marine microplastics carry potentially pathogenic Vibrio bacteria, finding Vibrio species on microplastic surfaces in seawater, raising concerns about plastics as vehicles for transporting harmful bacteria in marine environments.
Prediction of microplastic abundance in surface water of the ocean and influencing factors based on ensemble learning
Researchers used machine learning to predict microplastic levels in ocean surface waters and identify the key factors driving contamination. Their models found that geographic location, ocean currents, and proximity to populated coastlines were major predictors of microplastic abundance. This approach could help scientists map pollution hotspots without costly and time-consuming physical sampling.
Exploring the Composition and Functions of Plastic Microbiome Using Whole-Genome Sequencing
Whole-genome sequencing of microbial biofilms on four types of marine microplastics revealed that plastic surfaces harbor distinct microbial communities with unique functional potential, including enrichment of Vibrio species with pathogenic and plastic-degrading capabilities.
The attachment rate of Vibrio anguillarum strains to microplastics strongly varies with abiotic and biotic factors
Researchers studied how different factors affect the attachment of the fish pathogen Vibrio anguillarum to microplastics in marine environments. They found that bacterial attachment rates varied significantly depending on the plastic type, bacterial strain, and environmental conditions such as temperature and salinity. The findings suggest that microplastics could serve as vectors for pathogenic bacteria, though the risk depends on specific environmental and biological factors.
Bacterial biofilms colonizing plastics in estuarine waters, with an emphasis on Vibrio spp. and their antibacterial resistance
Scientists characterized bacterial biofilms colonizing plastic debris in estuarine waters, finding that plastics host distinct communities including Vibrio species with elevated antibiotic resistance compared to surrounding water.
Microplastic deposit predictions on sandy beaches by geotechnologies and machine learning models
Researchers used geotechnologies and machine learning models to predict microplastic deposition hotspots on sandy beaches, identifying environmental and anthropogenic variables that drive spatial variation in beach microplastic accumulation.
Machine Learning Prediction of Adsorption Behavior of Xenobiotics on Microplastics under Different Environmental Conditions
Researchers developed a machine learning model to predict how different xenobiotic chemicals adsorb onto microplastics under varying environmental conditions, providing a computational tool to assess microplastics as vectors for pollutant transport without requiring extensive laboratory experiments.
Exploring changes in microplastic-associated bacterial communities with time, location, and polymer type in Liusha Bay, China
Researchers tracked how bacterial communities colonizing different types of microplastics changed over time in an aquaculture bay in China. They found that both exposure duration and plastic type significantly influenced which bacteria grew on the surfaces, with hydrocarbon-degrading species becoming notably abundant. Concerning from a health perspective, the pathogenic bacterium Vibrio was detected on all microplastic samples, suggesting that floating plastics may serve as rafts for disease-causing organisms.
Understanding the mechanism of microplastic-associated antibiotic resistance genes in aquatic ecosystems: Insights from metagenomic analyses and machine learning
By analyzing large-scale genetic datasets with machine learning, researchers found that the type of microplastic strongly influences which bacteria grow on it and which antibiotic resistance genes those bacteria carry. Surprisingly, biodegradable plastics like PLA (often marketed as eco-friendly) posed a higher risk of harboring antibiotic resistance genes than conventional plastics, raising concerns about resistance spreading through water systems to humans.
Machine learning reveals microbial interactions driving plastic degradation across plastisphere environments
Using 16S rRNA sequencing and machine learning, this study characterized the microbial communities that colonize microplastics in ocean, river, and wastewater environments, revealing that wastewater plastispheres host the most diverse communities and carry the greatest density of potential plastic-degrading bacteria. Understanding which microbes interact to drive degradation could guide efforts to harness or engineer these communities to accelerate plastic breakdown.
Global distribution of marine microplastics and potential for biodegradation
Researchers created a global map predicting marine microplastic pollution using machine learning based on over 9,400 samples and assessed the potential for biodegradation using marine metagenome data. The study found that microplastics converge in subtropical gyres and polar seas, and identified marine microbial communities with genetic potential for plastic biodegradation, suggesting nature may offer partial solutions to this pollution problem.
Potential impact of marine-derived plastisphere as a Vibrio carrier on marine ecosystems: Current status and future perspectives
This review examines how microplastics in the ocean serve as floating platforms for Vibrio bacteria, which are significant pathogens threatening aquaculture and marine ecosystem health. Researchers found that the so-called plastisphere, the microbial community that colonizes plastic surfaces, can enhance the survival and spread of these harmful bacteria. The study highlights a concerning link between plastic pollution and the potential amplification of waterborne disease risks.
Dangerous Hitchhikers? Evidence for Potentially Pathogenic Vibrio Spp. on Microplastic Particles
Researchers collected microplastic particles from the North and Baltic Seas and found potentially pathogenic Vibrio bacteria growing on their surfaces, raising the possibility that microplastics could transport dangerous human pathogens to new areas. Vibrio species can cause serious intestinal illness in humans through contaminated water or raw seafood consumption.
Integrating metagenomics analysis and machine learning to identify drivers of antibiotic resistance genes abundance in microplastic-contaminated soil
Researchers integrated global soil metagenomic datasets with machine learning to identify which microplastic properties, climatic variables, and soil characteristics best predict antibiotic resistance gene (ARG) abundance in microplastic-contaminated soils. Microplastic type and surface area were stronger drivers of ARG enrichment than climate or soil chemistry, pointing to plastic material properties as key targets for antibiotic resistance management.
Predicting bacterial transport through saturated porous media using an automated machine learning model
Not relevant to microplastics — this study uses machine learning to predict the transport of E. coli bacteria through saturated soils, relevant to groundwater contamination from manure.
A preliminary study of the cultivable microbiota on the plastic litter collected by commercial fishing trawlers in the south-eastern Adriatic Sea, with emphasis on Vibrio isolates and their antibiotic resistance.
This study characterized the bacterial communities on plastic litter collected by fishing trawlers in the Adriatic Sea, finding distinct microbial assemblages on plastic compared to surrounding seawater and sediment, including Vibrio bacteria with concerning antibiotic resistance profiles. The results suggest that plastic debris can harbor and transport potentially harmful, antibiotic-resistant bacteria in marine environments.
Mapping the plastic legacy: Geospatial predictions of a microplastic inventory in a complex estuarine system using machine learning
Researchers applied machine learning techniques to develop geospatial predictions of microplastic inventory in a complex estuarine system, overcoming the limitations of coarse ocean basin models by accounting for the intricate geomorphological and hydrodynamic conditions that govern sediment-associated microplastic distribution.
Study of the impact of ocean warming on the expression of virulence factors in Vibrio parahaemolyticus and the response of the host Exaiptasia pallida to infection
Rising ocean temperatures are making the foodborne pathogen Vibrio parahaemolyticus more virulent, and this study shows that microplastics may be amplifying the threat by serving as surfaces on which these bacteria colonize and spread. Using a sea anemone model, the researchers explored how ocean warming and microplastic-associated pathogens together stress marine organisms. This is significant because microplastics acting as 'pathogen vectors' could increase the risk of seafood-borne illness for humans as ocean conditions change.
Microbial community niches on microplastics and prioritized environmental factors under various urban riverine conditions
Researchers manipulated organic content, salinity, and dissolved oxygen in bioreactors to assess which environmental factors most strongly shaped microbial communities colonizing microplastics in urban rivers. Dissolved oxygen and organic carbon content were identified as priority drivers of plastisphere community composition, with implications for predicting pathogen enrichment on MPs across river conditions.
From rivers to marine environments: A constantly evolving microbial community within the plastisphere
Researchers sampled 107 plastic pieces across four aquatic ecosystems in southern France and found that the sampling location and polymer chemistry were the strongest drivers of plastisphere microbial community composition, while only 11% of samples showed elevated Vibrio pathogen levels compared to surrounding water.
Plastics and Microplastics as Vectors for Bacteria and Human Pathogens
This study reviewed how marine plastic debris serves as a surface for bacterial colonization, including human pathogens, and examined the novel communities forming on plastic surfaces. The research raises public health concerns about microplastics acting as rafts that transport harmful bacteria to new locations, including to seafood and coastal recreational areas.
Predictive modeling of microplastic adsorption in aquatic environments using advanced machine learning models
Scientists used advanced machine learning models to predict how microplastics interact with and absorb organic pollutants in water. The results showed that microplastics with certain chemical properties attract more toxic compounds, which matters because contaminated microplastics in waterways can concentrate harmful chemicals that may eventually reach humans through drinking water and seafood.
Machine Learning to Predict the Adsorption Capacity of Microplastics
Researchers developed machine learning models to predict the adsorption capacity of microplastics for chemical pollutants, providing a computational tool to better understand how microplastics act as vectors for contaminant dispersal in aquatic environments.