An integrative data-centric approach to derivation and characterization of an adverse outcome pathway network for cadmium-induced toxicity DOI Open Access
Ajaya Kumar Sahoo, Nikhil Chivukula, K.H. Ramesh

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Dec. 13, 2023

Abstract Cadmium is a prominent toxic heavy metal that contaminates both terrestrial and aquatic environments. Owing to its high biological half-life low excretion rates, cadmium causes variety of adverse outcomes. Adverse outcome pathway (AOP) networks were envisioned systematically capture toxicological information enable risk assessment chemical regulation. Here, we leveraged AOP-Wiki integrated heterogeneous data from four other exposome-relevant resources build the first AOP network relevant for inorganic cadmium-induced toxicity. From AOP-Wiki, filtered 309 confidence AOPs, identified 312 key events (KEs) associated with cadmium, thereafter, curated 30 AOPs (cadmium-AOPs), using data-centric approach. By constructing undirected network, large connected component 18 cadmium-AOPs. Further, analyzed directed 59 KEs 82 event relationships (KERs) in largest graph-theoretic approaches. Subsequently, mined published literature artificial intelligence-based tools provide auxiliary evidence association all component. Finally, performed case studies verify rationality toxicity humans species. Overall, cadmium-AOP constructed this study will aid ongoing research systems toxicology exposome.

Language: Английский

An integrative data-centric approach to derivation and characterization of an adverse outcome pathway network for cadmium-induced toxicity DOI
Ajaya Kumar Sahoo, Nikhil Chivukula, K.H. Ramesh

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 920, P. 170968 - 170968

Published: Feb. 16, 2024

Language: Английский

Citations

11
Machine Learning‐Enabled Drug‐Induced Toxicity Prediction DOI Creative Commons
Changsen Bai, Lianlian Wu, Ruijiang Li

et al.

Advanced Science, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 3, 2025

Abstract Unexpected toxicity has become a significant obstacle to drug candidate development, accounting for 30% of discovery failures. Traditional assessment through animal testing is costly and time‐consuming. Big data artificial intelligence (AI), especially machine learning (ML), are robustly contributing innovation progress in toxicology research. However, the optimal AI model different types usually varies, making it essential conduct comparative analyses methods across domains. The diverse sources also pose challenges researchers focusing on specific studies. In this review, 10 categories drug‐induced examined, summarizing characteristics applicable ML models, including both predictive interpretable algorithms, striking balance between breadth depth. Key databases tools used prediction highlighted, toxicology, chemical, multi‐omics, benchmark databases, organized by their focus function clarify roles prediction. Finally, strategies turn into opportunities analyzed discussed. This review may provide with valuable reference understanding utilizing available resources bridge mechanistic insights, further advance application drugs‐induced

Language: Английский

Citations

1
Profiling assay performance in the DevTox germ layer reporter platform DOI Creative Commons
John T. Gamble, Chad Deisenroth

Current Research in Toxicology, Journal Year: 2025, Volume and Issue: 8, P. 100223 - 100223

Published: Jan. 1, 2025

The U.S. Environmental Protection Agency (U.S. EPA) is mandated to develop new approach methods (NAMs) detect chemicals risks susceptible populations, including effects on pregnant women and their offspring. With limited hazard information available for current chemicals, NAMs can provide greater relevance human biology, mechanistic insight, higher testing capacity than traditional animal models. DevTox Germ Layer Reporter (GLR) model platform was recently established high-throughput screening prioritization of potential developmental hazards. utilizes the RUES2-GLR pluripotent stem cell reporter line that expresses fluorescent fusion protein biomarkers SOX17 (endoderm), Brachyury (mesoderm), SOX2 (ectoderm pluripotency); enabling a multi-lineage readout gastrulation lineages. GLR-Endo assay used evaluate chemical differentiating endoderm, yielding balanced accuracy (BA) 72% against training set 43 toxicants 23 non-developmental toxicants. To assess predictivity additional early embryonic lineages, assays pluripotency (DevTox GLR-Pluri), ectoderm GLR-Ecto), mesoderm GLR-Meso) were developed. Chemical reference (12 4 toxicants) activity each revealed BAs 92% GLR-Pluri, 71% GLR-Ecto, 58% GLR-Meso. Expanded GLR-Pluri with 63 yielded 75% 68%, respectively. Amongst four GLR assays, maintained highest degree efficacy overall predictive compound evaluated in this study.

Language: Английский

Citations

0
A Simple Physiologically Based Toxicokinetic Model for Multi-Route In Vitro–In Vivo Extrapolation DOI
John F. Wambaugh, Celia Schacht, Caroline Ring

et al.

Environmental Science & Technology Letters, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 12, 2025

Many chemicals found in the environment and commerce have been characterized for potential hazards by using vitro screens. Translating concentrations that cause bioactivity into real-world exposures, other words, vitro–in vivo extrapolation (IVIVE), requires chemical-specific parameters mathematical models. An administered (for example, oral) equivalent dose rate (milligrams per kilogram day) causes steady-state human plasma (micromolar) to bioactive can be derived a simple IVIVE equation. Herein, we explain how this equation approximates physiologically based toxicokinetic (PBTK) model. Through derivation of solution PBTK model, show relevant flows tissues. We then extend modifying oral exposure model include gas inhalation exhalation. Gas exhalation increases clearance, potentially allowing more accurate prediction semivolatile organic chemicals. The revised equations also allow doses, parts million concentration would concentrations. comparison an new developed, describing exhaled doses.

Language: Английский

Citations

0
Intra-laboratory validation of yeast-based reporter gene assays for human thyroid hormone receptors DOI
Masahiro Ogawa,

Junya Kitamoto,

M. Nakashima

et al.

Journal of Pharmacological and Toxicological Methods, Journal Year: 2025, Volume and Issue: 132, P. 107593 - 107593

Published: Feb. 21, 2025

Language: Английский

Citations

0
Interpretation of thyroid-relevant bioactivity data for comparison to in vivo exposures: A prioritization approach for putative chemical inhibitors of in vitro deiodinase activity DOI
Kevin Truong,

J F Wambaugh,

Donald F. Kapraun

et al.

Toxicology, Journal Year: 2025, Volume and Issue: unknown, P. 154157 - 154157

Published: April 1, 2025

Language: Английский

Citations

0
Leveraging integrative toxicogenomic approach towards development of stressor-centric adverse outcome pathway networks for plastic additives DOI Open Access
Ajaya Kumar Sahoo, Nikhil Chivukula, Shreyes Rajan Madgaonkar

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: March 29, 2024

Abstract Plastics are widespread pollutants found in atmospheric, terrestrial and aquatic ecosystems due to their extensive usage environmental persistence. Plastic additives, that utilized achieve specific functionality plastics, leach into the environment upon plastic degradation pose considerable risk ecological human health. Limited knowledge concerning presence of additives throughout life cycle has hindered effective regulation, thereby posing risks product safety. In this study, we leveraged adverse outcome pathway (AOP) framework understand mechanisms underlying additives-induced toxicities. We first identified an exhaustive list 6470 from chemicals documented be plastics. Next, heterogenous toxicogenomics biological endpoints data five exposome-relevant resources, associations between 1287 322 complete high quality AOPs within AOP-Wiki. Based on these additive-AOP associations, constructed a stressor-centric AOP network, wherein stressors categorized 10 priority use sectors linked 27 disease categories. visualized additives-AOP network for each made them available dedicated website: https://cb.imsc.res.in/saopadditives/ . Finally, showed utility by identifying 28 highly relevant associated with benzo[a]pyrene, thereafter, explored toxicity pathways leading respiratory gastrointestinal system diseases humans developmental disorders species. Overall, will enable regulatory assessment contributing towards toxic-free circular economy

Language: Английский

Citations

3
A combination of high-throughput in vitro and in silico new approach methods (NAMs) for ecotoxicology hazard assessment for fish DOI Creative Commons
Johanna Nyffeler, Felix R. Harris, Clinton Willis

et al.

Environmental Toxicology and Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 6, 2025

Fish acute toxicity testing is used to inform environmental hazard assessment of chemicals. In silico and in vitro approaches have the potential reduce number fish increase efficiency generating data for assessing ecological hazards. Here, two bioactivity assays were adapted use high-throughput chemical screening. First, a miniaturized version Organisation Economic Co-operation Development (OECD) test guideline 249 plate reader-based assay RTgill-W1 cells was developed. Second, Cell Painting (CP) along with an imaging-based cell viability assay. Then, 225 chemicals tested each Potencies calls from reader comparable. The CP more sensitive than either that it detected larger as bioactive, phenotype altering concentrations (PACs) lower decreased viability. An disposition (IVD) model accounted sorption plastic over time applied predict freely dissolved PACs compared vivo data. Adjustment using IVD modeling improved concordance For 65 where comparison values possible, 59% adjusted within one order magnitude lethal 50% organisms. protective 73% This combination has or replace testing.

Language: Английский

Citations

0
Application of new approach methodology-derived points of departure with predicted or regulatory exposures to estimate bioactivity to exposure ratios (BER) for risk assessment DOI
Marilyn Silva

Human and Ecological Risk Assessment An International Journal, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 39

Published: Jan. 26, 2025

Language: Английский

Citations

0
Modeling omics dose-response at the pathway level with DoseRider DOI Creative Commons
Pablo Monfort‐Lanzas, Johanna M. Gostner, Hubert Hackl

et al.

Computational and Structural Biotechnology Journal, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

The generation of omics data sets has become an important approach in modern pharmacological and toxicological research as it can provide mechanistic quantitative information on a large scale. Analyses these frequently revealed non-linear dose-response relationship underscoring the importance modeling process to infer biological exposure limits. A number tools have been developed for various thresholds defined representation effect substance, such effective concentrations or benchmark doses (BMD). Here we present DoseRider easy-to-use web application companion R package linear assessment BMD at level pathways signatures using generalized mixed models. This allows analyze custom provided multi-omics RNA sequencing metabolomics its annotation collection gene from species. Moreover, introduce concept trend change (TCDs) numerical descriptor effects derived complex curves. usability was demonstrated by analyses bisphenol AF (BPAF) treatment human breast cancer cell line (MCF-7) 8 different chemical genetic perturbations (MSigDB). BPAF set genes upregulated estrogen 0.2 µM (95 %-CI 0.1-0.5 µM) lowest TCD (TCD1) 0.003 0.0006-0.01 µM). comprehensive presentation results underlines suitability system pharmacogenomics, toxicogenomics, applications beyond.

Language: Английский

Citations

0