We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Papers
20 resultsShowing papers similar to Exploring the prognostic implications of PET microplastic degradation products in colorectal cancer: insights from an integrated computational analysis on glucocorticoid pathway–mediated mechanisms
ClearExploring the prognostic implications of PET microplastic degradation products in colorectal cancer: insights from an integrated computational analysis on glucocorticoid pathway–mediated mechanisms
Researchers used network toxicology, machine learning, and molecular docking to investigate how PET degradation products—ethylene glycol and terephthalic acid—affect colorectal cancer prognosis through the glucocorticoid signaling pathway. The analysis identified 43 shared target genes, suggesting that PET breakdown products may worsen colorectal cancer outcomes by dysregulating glucocorticoid-mediated anti-inflammatory and cell survival signals.
Exploring the prognostic implications of PET microplastic degradation products in colorectal cancer: insights from an integrated computational analysis on glucocorticoid pathway–mediated mechanisms
This computational study investigated how PET microplastic degradation products affect colorectal cancer prognosis, identifying 43 genes linking ethylene glycol and terephthalic acid exposure to cancer pathogenesis via chronic inflammation mediated through TNF/IL-17 and glucocorticoid metabolic pathways.
The toxicological impact of PET-MPs exposure on atherosclerosis: insights from network toxicology, molecular docking, and machine learning
Researchers used network toxicology, molecular docking, and machine learning to identify how PET microplastics may promote atherosclerosis, narrowing 28 candidate targets to seven key genes and predicting interactions with atherosclerosis-relevant pathways including inflammation and lipid metabolism.
Polyethylene terephthalate microplastics exposure enhances the risk of ulcerative colitis: insights from multiomics integration, machine learning, and molecular docking reveal intestinal toxicity mechanisms
Using multiomics integration, machine learning, and molecular docking, this study identified mechanisms by which PET microplastic exposure may increase the risk of ulcerative colitis. Key pathways included intestinal barrier disruption, immune dysregulation, and oxidative stress triggered by PET-MP-protein interactions.
Integrative network toxicology and molecular docking preliminarily explore the potential role of polystyrene microplastics in childhood obesity
Researchers used computational methods including network toxicology, machine learning, and molecular docking to explore how polystyrene microplastics might contribute to childhood obesity. They identified 40 overlapping genes between obesity-related and microplastic-affected pathways, concentrated in lipid metabolism and insulin signaling. The study suggests that polystyrene microplastics may act as environmental triggers capable of disrupting metabolic balance by interacting with key regulatory genes.
Environmental PET-microplastic exposure and risk of non-alcoholic fatty liver disease: An integrated computational toxicology and multi-omics study
Researchers used computational toxicology and machine learning to identify six key genes linking PET microplastic exposure to non-alcoholic fatty liver disease (NAFLD), with the model achieving high diagnostic accuracy and molecular docking suggesting that PET-derived chemicals may directly bind to proteins controlling liver fat metabolism.
Leveraging integrative toxicogenomic approach towards development of stressor-centric adverse outcome pathway networks for plastic additives
Researchers applied integrative toxicogenomics to develop adverse outcome pathway networks for plastic additives that leach into the environment during plastic degradation. The study suggests that this approach can help systematically assess the health risks of chemical additives released from plastics across atmospheric, terrestrial, and aquatic ecosystems.
Integrated network toxicology, machine learning, molecular docking and experimental validation to elucidate mechanism of polyethylene terephthalate microplastics inducing periodontitis
Researchers combined computational biology, machine learning, and laboratory experiments to explore how polyethylene terephthalate microplastics might contribute to periodontitis, a common gum disease. They identified key molecular targets and signaling pathways through which microplastics could promote gum tissue inflammation. The study provides the first evidence linking microplastic exposure to the biological mechanisms underlying periodontal disease.
Integrative network toxicology and molecular docking preliminarily explore the potential role of polystyrene microplastics in childhood obesity
Researchers used an integrative computational approach combining cross-species transcriptomics, network toxicology, and molecular docking to investigate potential links between polystyrene microplastic exposure and childhood obesity. They identified shared gene targets involved in lipid metabolism and insulin signaling pathways, with molecular docking confirming stable binding between microplastic compounds and key metabolic proteins. The findings provide a preliminary molecular hypothesis suggesting microplastics could disrupt metabolic processes relevant to obesity.
Unveiling the pathogenic mechanisms of polyethylene terephthalate-microplastic-driven osteoarthritis and rheumatoid arthritis: PTGS2 signaling hub-oriented toxicity profiling
Researchers used computational analysis to investigate how PET microplastics might contribute to joint diseases like osteoarthritis and rheumatoid arthritis. They identified the PTGS2 gene, involved in inflammation, as a central hub connecting microplastic exposure to joint disease pathways. The study suggests that microplastics may worsen joint inflammation through specific molecular mechanisms, though further laboratory and clinical research is needed to confirm these computational findings.
Assessing the toxicological effects of exposure to environmental pollutants PET-MPs on vascular diseases: insights from network toxicology, molecular docking, molecular dynamics, and experimental validation
Researchers used network toxicology, molecular docking, and cell experiments to investigate how PET microplastics may contribute to vascular diseases. They identified four core molecular targets and found that PET microplastics induced mitochondrial oxidative stress, increased reactive oxygen species, and promoted vascular smooth muscle cell death. The study provides initial molecular-level evidence that microplastic exposure may be a contributing factor in vascular damage and remodeling.
In vitro evidence and integrative bioinformatics identify the SGLT2-PPARγ axis as a target against polyethylene microplastic-driven metabolic reprogramming in colorectal cancer cells
Researchers used in vitro experiments and bioinformatics to identify the SGLT2-PPARgamma axis as a molecular target affected by polyethylene microplastic exposure in colorectal cancer cells. The study suggests that microplastics may influence metabolic reprogramming in cancer cells, highlighting a potential interplay between environmental pollutants and metabolic regulation.
In-silico pharmacological insights into the therapeutic potential of microRNAs for microplastic-associated cancers
Researchers systematically screened published literature to identify cancer-related genes altered by microplastic exposure, then computationally evaluated microRNAs with anticancer activity that could target those genes, finding potential miRNA-based therapeutic candidates across breast, gastric, and other microplastic-associated tumor types.
Network toxicology and bioinformatics analysis reveal the molecular mechanisms of polyethylene terephthalate microplastics in exacerbating diabetic nephropathy
This computational study used bioinformatics to explore how polyethylene terephthalate (PET) microplastics might worsen diabetic kidney disease. The analysis identified key genes and inflammatory pathways that are affected by both PET microplastics and kidney damage in diabetes. The findings suggest that microplastic exposure could accelerate kidney problems in people who already have diabetes, though lab and clinical studies are needed to confirm this.
The impact of polyethylene terephthalate microplastics on the pathogenesis of atherosclerosis: Focusing on network toxicology and target gene detection
Researchers used network toxicology and gene analysis to investigate how PET microplastics may influence atherosclerosis, the buildup of plaque in arteries. They identified specific genes involved in inflammation and immune cell signaling that are affected by both PET exposure and atherosclerosis development. The study suggests that microplastic exposure could worsen cardiovascular disease through shared inflammatory pathways.
Polyethylene Terephthalate Microplastics Exposure Enhances the Risk of Ulcerative Colitis: Insights From Multi-Omics Integration, Machine Learning, and Molecular Docking Reveal Intestinal Toxicity Mechanisms: A Commentary
This commentary discusses a study linking polyethylene terephthalate (PET) microplastics to increased risk of ulcerative colitis, using machine learning, genomic analysis, and molecular docking. The authors raise methodological questions to help strengthen this emerging line of research connecting plastic exposure to gut inflammation.
Exploring the Potential Mechanism of Polyethylene Terephthalate Associated Cardiotoxicity through Network Toxicology and Molecular Docking
Researchers used computational approaches including network toxicology, molecular docking, and molecular dynamics simulations to explore how polyethylene terephthalate microplastics may affect cardiovascular function. The study identified potential molecular pathways through which PET exposure could contribute to cardiotoxicity. The findings provide a theoretical framework for understanding how plastic contaminants might interact with heart-related biological targets.
Mechanistic study of plastic monomers in gestational diabetes mellitus: A network toxicology and molecular docking approach
Using network toxicology and molecular docking, researchers investigated how plastic monomers interact with molecular targets involved in gestational diabetes mellitus (GDM). The analysis identified shared gene targets and signaling pathways linking plastic monomer exposure to insulin resistance and inflammatory mechanisms relevant to GDM development.
Evaluating the toxicological effects of PET-MPs exposure on atherosclerosis through integrated network toxicology analysis and experimental validation
Researchers used network toxicology analysis and laboratory experiments to investigate how polyethylene terephthalate microplastics may contribute to atherosclerosis. They identified several molecular targets and biological pathways through which these microplastics could promote plaque formation in blood vessels. The study provides preliminary evidence that a commonly encountered type of microplastic may interact with cardiovascular disease mechanisms, though further research is needed to confirm these findings.
Development of AOP relevant to microplastics based on toxicity mechanisms of chemical additives using ToxCast™ and deep learning models combined approach
Researchers used ToxCast high-throughput screening data and deep learning models to build adverse outcome pathway (AOP) models for common plastic additive chemicals, identifying molecular initiating events and potential health endpoints relevant to human and environmental microplastic toxicity.