Evidence map›Paper›PMID 32445755›Full record

ArticleToxicology and applied pharmacology2020

PBPK modeling of impact of nonalcoholic fatty liver disease on toxicokinetics of perchloroethylene in mice.

Chimeddulam Dalaijamts, Joseph A Cichocki, Yu-Syuan Luo, Ivan Rusyn, Weihsueh A Chiu

Open access · greenAbstract read
In one paragraph

Article in Toxicology and applied pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Synergistic toxicity in alcohol-associated liver disease and PFAS exposure.Toxicological sciences : an official journal of the Society of Toxicology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Chimeddulam DalaijamtsInterdisciplinary Faculty of Toxicology, Texas A&M University, College Station, TX, USA; Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA.
Joseph A CichockiInterdisciplinary Faculty of Toxicology, Texas A&M University, College Station, TX, USA; Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA.
Yu-Syuan LuoInterdisciplinary Faculty of Toxicology, Texas A&M University, College Station, TX, USA; Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA.
Ivan RusynInterdisciplinary Faculty of Toxicology, Texas A&M University, College Station, TX, USA; Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA.
Weihsueh A ChiuInterdisciplinary Faculty of Toxicology, Texas A&M University, College Station, TX, USA; Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA. Electronic address: WChiu@cvm.tamu.edu.
Texas A&M University · US

Funding

Single cell, multi-parametric high throughput platform to classify endocrine disruptor potential of mixturesP42ES027704 · NIEHS · TEXAS A&M UNIVERSITY · PI Efstratios Pistikopoulos · 2017 to 2026
$21.2M
Texas A&M Center for Environmental Health Research (TiCER)P30ES029067 · NIEHS · TEXAS A&M UNIVERSITY · PI Galen Newman · 2019 to 2026
$13.0M
Nonalcoholic steatohepatitis as a potential contributor to individual susceptibility to tetrachloroethylene-associated toxicityF32ES026005 · NIEHS · TEXAS A&M UNIVERSITY · PI CICHOCKI, JOSEPH · 2015 to 2016
$88k
NIEHS NIH HHS F32 ES026005NIEHS NIH HHS P30 ES029067NIEHS NIH HHS P42 ES027704
6 · The paper itself

Abstract

backgroundNonalcoholic fatty liver disease (NAFLD), a major cause of chronic liver disease in the Western countries with increasing prevalence worldwide, may substantially affect chemical toxicokinetics and thereby modulate chemical toxicity.

objectivesThis study aims to use physiologically-based pharmacokinetic (PBPK) modeling to characterize the impact of NAFLD on toxicokinetics of perchloroethylene (perc).

methodsQuantitative measures of physiological and biochemical changes associated with the presence of NAFLD induced by high-fat or methionine/choline-deficient diets in C57B1/6 J mice are incorporated into a previously developed PBPK model for perc and its oxidative and conjugative metabolites. Impacts on liver fat and volume, as well as blood:air and liver:air partition coefficients, are incorporated into the model. Hierarchical Bayesian population analysis using Markov chain Monte Carlo simulation is conducted to characterize uncertainty, as well as disease-induced variability in toxicokinetics.

resultsNAFLD has a major effect on toxicokinetics of perc, with greater oxidative and lower conjugative metabolism as compared to healthy mice. The NAFLD-updated PBPK model accurately predicts in vivo metabolism of perc through oxidative and conjugative pathways in all tissues across disease states and strains, but underestimated parent compound concentrations in blood and liver of NAFLD mice.

conclusionsWe demonstrate the application of PBPK modeling to predict the effects of pre-existing disease conditions as a variability factor in perc metabolism. These results suggest that non-genetic factors such as diet and pre-existing disease can be as influential as genetic factors in altering toxicokinetics of perc, and thus are likely contribute substantially to population variation in its adverse effects.

Indexed as

Models, BiologicalAnimalsBayes TheoremLiverMaleMetabolic Clearance RateMiceMice, Inbred C57BLNon-alcoholic Fatty Liver DiseaseOxidative StressTetrachloroethyleneToxicokineticsTetrachloroethyleneBayesian analysisNonalcoholic Fatty Liver Disease (NAFLD)PBPKPerchloroethylenePopulation variationToxicokinetics

Identifiers

PMID32445755
PMCPMC7339121
OpenAlexW3027991966

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.