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Results for “network toxicology”

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At least 19 recordsLinked to original sources

PubMed2026

Toxicological effects of propyl 4-hydroxybenzoate on gallstone pathogenesis: An integrated mendelian randomization, network toxicology, and experimental study.

BACKGROUND: Gallstone disease is a prevalent digestive disorder with substantial global socioeconomic burden. Propyl 4-hydroxybenzoate (PP), a widely used paraben preservative, exhibits potential metabolic and hepatic toxicity, yet its role in gallstone pathogenesis remains unclear. This study aimed to explore the causal association between PP exposure and gallstone formation and the underlying mechanism. METHODS: Two-sample Mendelian randomization (MR) was performed using genome-wide association study (GWAS) data. Network toxicology, molecular docking, and molecular dynamics simulation were applied to screen for core targets. In vivo experiments, transcriptome sequencing, Western blot (WB), and ELISA were conducted for mechanistic validation. RESULTS: MR confirmed a causal link between circulating PP levels and an elevated risk of gallstones (P < 0.05), with AKT1 identified as the key target. In mice, PP aggravated gallstone formation by activating the AKT1-NF-κB-CXCL1 pathway, enhancing hepatic inflammation and neutrophil extracellular traps (NETs) formation; these effects were reversed by AKT inhibition. CONCLUSION: PP promotes gallstone formation via the AKT1-NF-κB-CXCL1-NETs axis. Our findings highlight PP as an environmental risk factor for gallstones, providing novel insights into their prevention and targeted therapy.

Animals↗

PubMed2026

Multitarget interactions of bisphenol A in polycystic ovary syndrome: evidence from integrated network toxicology, mendelian randomization, and molecular docking.

OBJECTIVE: To study the potential pathogenic mechanisms of bisphenol A (BPA) in polycystic ovary syndrome (PCOS) using an integrative computational strategy. DESIGN: Integrative computational study combining network toxicology, Mendelian randomization (MR), and molecular docking. SUBJECTS: For MR analysis, genetic data were sourced from large European-ancestry cohorts, including plasma protein quantitative trait loci data and genome-wide association study summary statistics for PCOS (3,045 cases and 267,780 controls). EXPOSURE: In silico exposure to BPA for target prediction; genetically predicted plasma protein levels for causal inference. MAIN OUTCOME MEASURES: Identification of overlapping targets between BPA and PCOS; functional enrichment pathways; causal effects of prioritized proteins on PCOS risk (odds ratios with 95% confidence intervals); binding affinities between BPA and core targets (kcal/mol). RESULTS: Network toxicology identified 310 overlapping targets between BPA and PCOS. Enrichment analyses revealed significant involvement in endocrine signaling, inflammatory pathways (eg, IL-17), and cellular processes. MR demonstrated that genetically elevated levels of RET, CXCL8, HTR6, MMP1, MMP9, NTRK1, and TNNI2 were significantly associated with increased PCOS risk, whereas higher PSAP and SHBG levels were protective. Molecular docking confirmed stable binding between BPA and all nine key targets, with strongest affinity for SHBG (-8.4 kcal/mol), followed by NTRK1, TNNI2, and RET. CONCLUSION: This integrative investigation suggests that BPA may contribute to PCOS pathogenesis through multitarget interactions involving inflammatory mediators, endocrine regulators, and tissue remodeling proteins. The findings provide prioritized targets and mechanistic insights for future experimental validation and environmental risk assessment.

Female↗

PubMed2026

Analysis of the molecular mechanism underlying di(2-ethylhexyl) phthalate-induced bladder carcinogenesis via network toxicology and molecular docking approaches: An observational study.

This study aims to investigate the toxicity of di(2-ethylhexyl) phthalate (DEHP) and the potential molecular mechanisms of DEHP-induced bladder cancer (BLCA) using network toxicology and molecular docking strategies. The toxicity of DEHP was assessed using Prox-II software, and potential targets for DEHP-induced BLCA were identified by integrating data from ChEMBL database, Search Tool for Interactions of Chemicals, SwissTargetPrediction, GeneCards, Therapeutic Target Database, Online Mendelian Inheritance in Man, and The Cancer Genome Atlas. STRING database and Cytoscape were employed to construct target networks and determine core targets. The expression levels of core targets were analyzed using R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on potential and core targets. Molecular docking was carried out using CB-Dock 2 to verify the interactions between DEHP and core targets. A total of 105 potential targets related to DEHP-induced BLCA were identified, from which 7 core targets were selected: cyclin-dependent kinase 1, interleukin 6, cyclin-dependent kinase 2, cyclin B1, Erb-B2 receptor tyrosine kinase 2, cyclin B2, and B-cell lymphoma 2. IL-6 and B-cell lymphoma 2 showed downregulated expression in tumor tissues, while cyclin-dependent kinase 1, cyclin-dependent kinase 2, cyclin B1, Erb-B2 receptor tyrosine kinase 2, and cyclin B2 were upregulated. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that these targets were enriched in cell signaling and cancer-related pathways. Molecular docking confirmed that DEHP interacts with these core targets. DEHP may promote the development of BLCA by interacting with key proteins and signaling pathways. This study provides a theoretical basis for understanding the molecular mechanisms of DEHP-induced BLCA and offers references for future prevention and treatment strategies.

Diethylhexyl Phthalate↗

PubMed1988

Joint Toxicology Network at the Latin American Regional Level.

The Environmental Health Program of the Pan American Health Organization has established goals to be able to comply with the resolutions of the Board of Directors and the Executive Committee. As an integral part of the Environmental Health Program, the Pan American Center for Human Ecology and Health (ECO) must contribute to the achievement of these goals. Generally speaking, there is a scarcity of toxicology professionals in the Region of the Americas. In order to ameliorate this situation, it is suggested that activities in the areas of training professionals, conducting research, dissemination of information, and publishing of educational materials be undertaken. It is proposed that the "Joint Toxicology Network at the Regional Level" be created. The objectives of such a network would be the promotion and encouragement of activities in the area of toxicology; assistance to countries in identifying their needs; encouragement of information exchange, publication and training in toxicology; and support of the Toxicology Information Centers. In order to achieve the Network objectives, it is suggested that activities be undertaken by the national groups belonging to the network.

Environmental Health↗

PubMed2025

Exploring potential targets and molecular mechanisms of traumatic brain injury exacerbated by Benzo(a)pyrene via network toxicology and molecular dynamics simulation.

Benzo(a)pyrene (BaP) is a common environmental pollutant from combustion sources that promotes oxidative stress, neuroinflammation and disruption of blood-brain barrier (BBB). However, its contribution to worsening traumatic brain injury (TBI) remains unclear. In this study, we aimed to assess the contribution of BaP to secondary injury in TBI. By integrating data from e.g., the Comparative Toxicogenomics Database, GeneCards, and Online Mendelian Inheritance in Man, 121 overlapping core targets were identified between BaP and TBI. Enrichment analyses via Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, combined with protein-protein interaction networks and topological algorithms (degree, closeness centrality, betweenness centrality, average shortest path length, topological coefficient and partner of multi-edged node pairs), highlighted five hub genes (TP53, EGFR, AKT1, ACTB, and TNF) implicated in mitogen-activated protein kinase signaling, oxidative stress, and neuroinflammation. Molecular docking showed strong binding affinities of BaP to these hub proteins, with energies from -9.3 to -12.1 kcal/mol, tighter than co-crystal ligands and existing protein-binding drugs. Molecular dynamics simulations confirmed interaction stability through low root-mean-square deviation (< 0.5 nm), fluctuation, and radius of gyration values. Calculation of binding free energies using MM-PBSA validated the strong binding affinity between BaP and binding pockets of each hub genes. Toxicity prediction analysis revealed an oral LD50 of 316 mg/kg for BaP, with high probabilities for neurotoxicity, BBB permeability, carcinogenicity, and mutagenicity, associated with aryl hydrocarbon receptor activation. These findings reveal a "neurovascular homeostasis disruption" network underlying BaP-exacerbated TBI pathology and highlight potential targets to reduce pollution-related risks in TBI management.

Benzo(a)pyrene↗

PubMed2026

Investigating the mechanisms of PhIP-induced colorectal cancer through network toxicology, machine learning, and molecular dynamics simulation.

BACKGROUND: Over the past few years, 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP)- a compound from grilled or processed meats-has emerged as a major player in cancer development, especially colorectal cancer (CRC). This work dives into its potential links to CRC and uncovers the key genes that bridge this connection. METHODS: We tapped into various databases to pinpoint target genes tied to PhIP and CRC, then ran protein-protein interaction (PPI) analyses for visualization. Next, we explored underlying mechanisms through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. To nail down predictions, we tested 107 machine learning pipelines and picked the best one, validating its accuracy and the core genes' prognostic value across datasets. Next, molecular docking and dynamics simulations probed the interactions between these genes and PhIP. Finally, cell proliferation was assessed using Cell Counting Kit-8 (CCK-8) and 5-ethynyl-2'-deoxyuridine (EdU) assays, and polymerase chain reaction (PCR) was performed to validate the expression levels of the hub genes. RESULTS: Our analysis identified 39 overlapping genes, from which a machine learning model (glmBoost + Enet) identified six candidate targets: CDK4, CEBPB, COMT, SOX9, TIMP1, and TOP2A. To prioritize these, a hierarchical screening framework was applied. Molecular docking and dynamics simulations identified CDK4, COMT, and TIMP1 as the most stable interactors with PhIP. Functional assays confirmed that PhIP treatment significantly enhanced the proliferation of CRC cells. Crucially, quantitative PCR (qPCR) validation in multiple CRC cell lines identified TIMP1 as the primary target, showing the most consistent and significant upregulation upon PhIP exposure. CONCLUSIONS: In essence, these genes drive PhIP is role in CRC, offering novel insights into its molecular pathways. This could reshape how we tackle food-related pollutants, paving the way for better prevention and targeted therapies.

Colorectal cancer (CRC)↗

PubMed2000

Canadian Network of Toxicology Centres (CNTC) executive summary--annual research symposium, 29-30 March 1999.

Explore the source record for details and available documents.

Canada↗

PubMed2005

Latin America's present and future challenges in toxicology education.

Industrialization that Latin America has experienced during the past 50 years, the increase of population and the growth of chemical-related industries has generated a variety of environmental problems that must be addressed. After assessing these profound changes, greater emphasis should be placed on the study of environmental health and toxicology. Latin American countries face many problems that are common to other developing nations. Therefore, there is a demand for safety assessment and regulatory control of chemicals that create a need for increasing numbers of toxicologists. To meet this demand, educational programs in toxicology have to be designed. This paper utilizes a consultation questionnaire that includes toxicology-network members, scientists and educational institutions where toxicology is taught. An analysis of the information collected is made, with an emphasis on what we currently lack and on future challenges for toxicology professionals. Although the response from the study institutions was 65% (13 countries out of 20), the paper aims to assess the present situation of toxicology. The convenience for a certification/recognition for toxicologists is also evaluated. Action needs to be taken to promote scientific development based on regional specific needs that require increasing at the number of toxicology programs, and promoting of cooperation between academics and researchers. Among the limitations we have are the variability of curricula, objectives and priorities. The increasing globalization of markets and regulations requires the harmonization of graduate/postgraduate programs to ensure that risk assessment and management are dealt with uniformly. Cooperation among our countries and international assistance should play a more prominent role in the promotion of regional integration and the more efficient utilization of international experience in defining educational policies.

Latin America↗

PubMed2026

Screening of core targets for Di(2-ethylhexyl) Phthalate-related gastric cancer based on machine learning, molecular docking, and SHAP analysis.

PURPOSE: Given the existing uncertainties regarding the link between Di(2-ethylhexyl) phthalate (DEHP) exposure and gastric cancer (GC) progression, this study aimed to clarify their association, identify the toxic targets of DEHP, and elucidate the underlying molecular mechanisms. METHODS: Multiple integrated approaches were employed, including Gene Expression Omnibus (GEO) data analysis, network toxicology, molecular docking, and machine learning. STRING and Cytoscape tools were utilized to identify key targets, while Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the functional enrichment of intersecting targets. Machine learning and SHAP analysis were applied to screen core targets in GC. Molecular docking was performed to evaluate the binding affinity of DEHP toward core targets, and 200 ns molecular dynamics simulations were further conducted for representative complexes to validate their dynamic stability. RESULTS: A total of 18 key targets were identified using STRING and Cytoscape. GO and KEGG enrichment analyses demonstrated that these intersecting targets were primarily enriched in the extracellular region, as well as the Calcium signaling pathway and cAMP signaling pathway. Through machine learning analyses, 7 key genes (ADRB2, ESRRG, GRIA4, IL13RA2, NR3C2, PLA2G1B, and SULT2A1) were identified as core targets in GC through machine learning analyses. Molecular docking simulations revealed strong binding specificity between DEHP and the target proteins. Among them, NR3C2 and ADRB2 exhibited relatively high predictive importance in the machine learning models. DEHP showed favorable binding affinity toward these core targets, and molecular dynamics simulations further confirmed that ADRB2-DEHP and NR3C2-DEHP complexes maintained stable conformations throughout the simulation. CONCLUSIONS: Our findings identified GC associated genes that were computationally predicted as potential targets of DEHP. These results indicated structural compatibility between DEHP and its target proteins but did not prove that DEHP exposure accounts for the gene expression changes in GC.

Molecular Docking Simulation↗

PubMed1998

Mosquitoes and mosquito repellents: a clinician's guide.

This paper is intended to provide the clinician with the detailed and scientific information needed to advise patients who seek safe and effective ways of preventing mosquito bites. For this review, clinical and analytical data were selected from peer-reviewed research studies and review articles, case reports, entomology texts and journals, and government and industry publications. Relevant information was identified through a search of the MEDLINE database, the World Wide Web, the Mosquito-L electronic mailing list, and the Extension Toxicology Network database; selected U.S. Army, U.S. Environmental Protection Agency, and U.S. Department of Agriculture publications were also reviewed. N,N-diethyl-3-methylbenzamide (DEET) is the most effective, and best studied, insect repellent currently on the market. This substance has a remarkable safety profile after 40 years of worldwide use, but toxic reactions can occur (usually when the product is misused). When DEET-based repellents are applied in combination with permethrin-treated clothing, protection against bites of nearly 100% can be achieved. Plant-based repellents are generally less effective than DEET-based products. Ultrasonic devices, outdoor bug "zappers," and bat houses are not effective against mosquitoes. Highly sensitive persons may want to take oral antihistamines to minimize cutaneous reactions to mosquito bites.

Animals↗

PubMed1980

The Drug Abuse Warning Network (DAWN) Program. Toxicologic verification of 1,008 emergency room 'mentions'.

One thousand eight emergency room patient records from which reports were contributed to the federal Drug Abuse Warning Network (DAWN) system from the Los Angeles County/University of Southern California Medical Center in 1977 were studied. The drugs reported to DAWN for these patients were compared with the available toxicology laboratory reports for some of these same patients. The purpose was to test the validity of the data reported to DAWN. Toxologic analyses had been performed on only 528 patients (52%) of the entire sample. Eighty percent of these tested had some positive toxicology result. The DAWN reports were verified in 20% of the tested sample, found to be incorrect in 11%, and partially correct or partially incorrect in 69%. Drugs identified toxicologically had varied concentrations, some below or within therapeutic range and some at toxic levels. This study suggests that the reliability of DAWN REPORTS SHOULD BE TESTed prospectively in an unbiased definitive material study.

Alcohol Drinking↗

PubMed1993

The underreporting of cocaine-related trauma: drug abuse warning network reports vs hospital toxicology tests.

OBJECTIVE: The purpose of this study was to assess whether cocaine-related trauma is underreported to the US Federal Drug Abuse Warning Network (DAWN). METHODS: We compared DAWN reports filed by an urban emergency department with the department's toxicology results for patients treated for major trauma. DAWN regulations in effect during the study period required the reporting of all patients treated for injury who used drugs or who tested positive for drugs of abuse. RESULTS: Of 520 patients treated for major trauma, 217 (42%) were tested for a variety of drugs. Of these, 82 (38%) tested positive for cocaine. Of the 102 patients injured in motor vehicle accidents, 20 (20%) tested positive for cocaine. Of the 59 patients injured in motor vehicle accidents who were under age 40, 18 (30%) tested positive for cocaine. Of 100 victims of violent assault, 57 tested positive for cocaine. During the time period studied, DAWN recorded 48 hospital visits associated with cocaine, none involving trauma or injury. CONCLUSIONS: Cocaine-related trauma was unreported to DAWN despite the hospital's compliance with the system's guidelines. The pattern of DAWN reports from other institutions suggests that underreporting of cocaine-related injury is widespread.

Accidents↗

PubMed2006

Validation of counter propagation neural network models for predictive toxicology according to the OECD principles: a case study.

The OECD has proposed five principles for validation of QSAR models used for regulatory purposes. Here we present a case study investigating how these principles can be applied to models based on Kohonen and counter propagation neural networks. The study is based on a counter propagation network model that has been built using toxicity data in fish fathead minnow for 541 compounds. The study demonstrates that most, if not all, of the OECD criteria may be met when modeling using this neural network approach.

Animal Use Alternatives↗

PubMed1995

Hazardous substances data bank (HSDB) as a source of environmental fate information on chemicals.

The Hazardous Substances Data Bank (HSDB), a factual data bank on the National Library of Medicine's (NLM) TOXNET (Toxicology Data Network) online system, provides information in areas such as chemical substance identification, chemical and physical properties, safety and handling, toxicology, pharmacology, environmental fate and transformation, regulations, and analytical methodology. This article discusses how environmental fate data is handled in HSDB.

Animals↗

PubMed1990

Toxicological information series, IV. Information resources for chemical emergency response.

The need for rapidly available information by community agencies responding to chemical emergencies (leaks, spills, releases, fires, explosions, etc.) can be met by a number of resources. These resources include local poison control centers, the Toxicology Data Network (National Library of Medicine), the Agency for Toxic Substances and Disease Registry, ATSDR/NLM's ANSWER, the National Chemical Response and Information Center, the National Pesticide Telecommunications Network, The National Response Center (U.S. Coast Guard), the Federal Emergency Management Agency, the U.S. Environmental Protection Agency, the National Safety Council, private-sector database vendors, and textbooks addressing hazardous substances.

Emergencies↗

PubMedDate not supplied

Toxicological and environmental health information from the National Library of Medicine.

The National Library of Medicine's Toxicology and Environmental Health Information Program is the outgrowth of a 1966 document on "Handling of Toxicological Information," prepared by the Presidents Science Advisory Committee (National Library of Medicine, 1995). The Toxicology and Environmental Health Program is responsible for the creation and deployment of both bibliographic and factual files concerned with toxicology, carcinogenesis, developmental and reproductive effects of chemical substances, toxic chemical releases, and the medical and environmental behavior of chemical substances. The two main computer systems that provide bibliographic and factual data banks are Toxicology Data Network (TOXNET) and ELHILL. A number of the files found in the TOXNET system are built and maintained by other federal agencies such as the National Cancer Institute, the U.S. Environmental Protection Agency, the National Institute for Occupational Safety and Health.

Animals↗

PubMed2001

Metabonomic characterization of genetic variations in toxicological and metabolic responses using probabilistic neural networks.

Current emphasis on efficient screening of novel therapeutic agents in toxicological studies has resulted in the evaluation of novel analytical technologies, including genomic (transcriptomic) and proteomic approaches. We have shown that high-resolution 1H NMR spectroscopy of biofluids and tissues coupled with appropriate chemometric analysis can also provide complementary data for use in in vivo toxicological screening of drugs. Metabonomics concerns the quantitative analysis of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification [Nicholson, J. K., Lindon, J. C., and Holmes, E. (1999) Xenobiotica 11, 1181-1189]. In this study, we have used 1H NMR spectroscopy to characterize the time-related changes in the urinary metabolite profiles of laboratory rats treated with 13 model toxins and drugs which predominantly target liver or kidney. These 1H NMR spectra were data-reduced and subsequently analyzed using a probabilistic neural network (PNN) approach. The methods encompassed a database of 1310 samples, of which 583 comprised a training set for the neural network, with the remaining 727 (independent cases) employed as a test set for validation. Using these techniques, the 13 classes of toxicity, together with the variations associated with strain, were distinguishable to >90%. Analysis of the 1H NMR spectral data by multilayer perceptron networks and principal components analysis gave a similar but less accurate classification than PNN analysis. This study has highlighted the value of probabilistic neural networks in developing accurate NMR-based metabonomic models for the prediction of xenobiotic-induced toxicity in experimental animals and indicates possible future uses in accelerated drug discovery programs. Furthermore, the sensitivity of this tool to strain differences may prove to be useful in investigating the genetic variation of metabolic responses and for assessing the validity of specific animal models.

Animals↗

PubMed2026

Exploring the mechanism of Acanthopanax in treating vertigo: A network pharmacology and molecular docking study.

Acanthopanax has therapeutic efficacy against vertigo; however, the underlying mechanism remains unclear. This study aimed to elucidate the mechanism by which Acanthopanax treats vertigo through integrated network pharmacology and molecular docking techniques, and retrieved all target genes of Acanthopanax for vertigo treatment from July to October 2025. Vertigo-related target genes were subsequently identified from public databases, including GeneCards and Online Mendelian Inheritance in Man. The intersection between Acanthopanax-derived targets and vertigo-related targets was analyzed to identify candidate target genes. Using the STRING platform, we constructed protein-protein interaction networks for the identified candidate targets and mined the core functional modules within these networks. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on candidate targets via the clusterProfiler package. A carp bile poisoning-liver injury target-pathway network was constructed via Cytoscape 3.8.2 software, network topology analysis was conducted, and the core components and targets were screened. The results found that A total of 295 candidate targets for the treatment of vertigo caused by Eleutherococcus senticosus were identified. Pathway enrichment analysis revealed that Eleutherococcus senticosus treatment for vertigo may be closely associated with pathways related to IL-17, TNF, phosphoinositide 3-kinase (PI3K)-Akt, p53, HIF-1, and Forkhead box O signaling. The core targets for the treatment of A. senticosus vertigo include TP53, AKT1, STAT3, TNF, and JUN. Network pharmacology and molecular docking studies suggest that A. senticosus may treat vertigo by regulating targets such as JUN, TNF, AKT1, STAT3, and STAT3 through pathways such as the IL-17, TNF, phosphoinositide 3-kinase-Akt, p53, HIF-1, and Forkhead box O signaling pathways. These mechanisms warrant further investigation in future o and in vitro studies.

Molecular Docking Simulation↗