We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Environmental Toxicology: Modern Approaches for Assessing Ecological and Human Health Risks
AI summary Read the abstract
This review paper rounds up how scientists are getting better at studying pollution's effects on our bodies and the environment, including growing concerns about microplastics and "hormone-disrupting" chemicals that can build up in our food and mess with our cells. Instead of relying mainly on animal testing, researchers are now using lab-grown mini-organs, computer modeling, and AI to more quickly and accurately predict which chemicals are dangerous—helping regulators make smarter, faster decisions to protect public health as pollution and climate change increasingly interact in new ways.
ABSTRACT Environmental toxicology has advanced significantly to address the increasing complexity of pollutants that affect both ecosystems and human health. The emerging contaminants such as microplastics and endocrine disrupting chemicals present significant risks due to their potential for bioaccumulation and biomagnification within food chains. These pollutants can induce significant physiological disturbances including oxidative stress, hormonal imbalance and other cellular alterations. Furthermore, climate driven changes such as temperature fluctuations and extreme weather events influence the distribution, persistence and toxicity of environmental contaminants. These factors often interact with biological stressors, intensifying ecological impacts and emphasising the need for adaptive environmental management strategies. Environmental toxicology is witnessing a paradigm shift from conventional animal- based testing to innovative methodological approaches. High - throughput in vitro screening, organ - on - a chip technology that mimic tissue level interactions and computational toxicology are transforming toxicological research. Artificial Intelligence and Machine Learning are increasingly used to predict toxicant fate, identify exposure pathways, and evaluate long - term ecological consequences. These technologies help prioritise chemicals for testing, while reducing research costs, and ethical concerns associated with animal experimentation. Modern risk assessment frameworks now integrate genomics, proteomics and metabolomics with agent- based ecological modelling to enable the identification of system level biological responses, including epigenetic modifications associated with pollution related diseases. Such integrative approaches support evidence-based regulatory decisions, guiding emission control policies and promoting sustainable bioremediation strategies for safeguarding ecosystems and public health. The integration of data-driven technologies, non-animal experimental models, and multi-scale ecological modelling is redefining environmental toxicology. These advances enhance the ability to anticipate and mitigate emerging environmental threats, ultimately contributing to the protection of ecosystem integrity and public health in a rapidly changing global environment.
More Papers Like This
Environmental Toxicology: Modern Approaches for Assessing Ecological and Human Health Risks
AI summary Read the abstract
This review paper explains how scientists are updating the tools they use to study pollution's effects on our bodies and the environment—including newer threats like microplastics and hormone-disrupting chemicals that can build up in the food chain and cause issues like cellular stress and hormone imbalances. Instead of relying mainly on animal testing, researchers are now using lab-grown tissue models, AI, and genetic analysis to more quickly and accurately predict which chemicals are risky, helping regulators make faster, evidence-based decisions to protect public health.
Enhancing Chemical Safety and Toxicology Through AI
AI summary Read the abstract
This review paper explains how AI tools are making it faster and more reliable to predict whether chemicals are safe, reducing the need for animal testing while still following strict scientific standards. This matters because it could speed up how quickly we identify harmful substances—including microplastics—in our environment and everyday products, giving regulators better tools to protect public health before problems occur.
Human organoids to assess environmental contaminants toxicity and mode of action: towards New Approach Methodologies
AI summary Read the abstract
This review explores how human organoids, miniature lab-grown organ models, can be used to test the toxicity of environmental contaminants including microplastics. These 3D tissue models offer a more accurate picture of how pollutants affect human cells than traditional lab tests, though more work is needed to simulate the chronic, low-dose exposures people actually experience.
Current Advances in Aquatic and Marine Toxicology
AI summary Read the abstract
This review paper summarizes current research on how pollution affects water environments and the animals living in them. Scientists are finding that new types of pollution like microplastics, medicines in water, and tiny manufactured particles are creating health risks that we don't fully understand yet. This matters because these pollutants can end up in our drinking water and the fish we eat, potentially affecting human health.
Artificial intelligence for microplastic pollution monitoring, predictive modeling, and risk assessment: advances, challenges, and future perspectives
AI summary Read the abstract
This review paper explains how artificial intelligence is helping scientists detect, track, and analyze microplastics faster and more accurately than older lab methods allow. This matters because better detection tools could speed up efforts to understand how these tiny plastic particles spread through our environment, food, and bodies, ultimately supporting stronger health protections and cleanup strategies.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.