Evidence map›Paper›PMID 25858911›Full record

ArticleToxicological sciences : an official journal of the Society of Toxicology2015

Comparative Risks of Aldehyde Constituents in Cigarette Smoke Using Transient Computational Fluid Dynamics/Physiologically Based Pharmacokinetic Models of the Rat and Human Respiratory Tracts.

Richard A Corley, Senthil Kabilan, Andrew P Kuprat, James P Carson, Richard E Jacob, Kevin R Minard, Justin G Teeguarden, Charles Timchalk, Sudhakar Pipavath, Robb Glenny and 1 more

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Toxicological sciences : an official journal of the Society of Toxicology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
4.2field-weighted citation impact, top 6% 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

26 citing papers in PubMed, 74 citations in OpenAlex.

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  19. Article
  20. Computational Analysis of Deposition and Translocation of Inhaled Nicotine and Acrolein in the Human Body with E-cigarette Puffing Topographies.Aerosol science and technology : the journal of the American Association for Aerosol Research · 2018
    Article
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

11 authors at 3 institutions in 1 country.

Richard A Corley*Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352; Texas Advanced Computing Center, University of Texas, Austin, Texas 78758; Radiology, University of Washington, Seattle, Washington 98195; and Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, Washington 98195 rick.corley@pnnl.gov.
Senthil Kabilan*Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352; Texas Advanced Computing Center, University of Texas, Austin, Texas 78758; Radiology, University of Washington, Seattle, Washington 98195; and Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, Washington 98195.
Andrew P Kuprat*Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352; Texas Advanced Computing Center, University of Texas, Austin, Texas 78758; Radiology, University of Washington, Seattle, Washington 98195; and Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, Washington 98195.
James P Carson*Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352; Texas Advanced Computing Center, University of Texas, Austin, Texas 78758; Radiology, University of Washington, Seattle, Washington 98195; and Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, Washington 98195.
Richard E Jacob*Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352; Texas Advanced Computing Center, University of Texas, Austin, Texas 78758; Radiology, University of Washington, Seattle, Washington 98195; and Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, Washington 98195.
Kevin R Minard*Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352; Texas Advanced Computing Center, University of Texas, Austin, Texas 78758; Radiology, University of Washington, Seattle, Washington 98195; and Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, Washington 98195.
Justin G Teeguarden*Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352; Texas Advanced Computing Center, University of Texas, Austin, Texas 78758; Radiology, University of Washington, Seattle, Washington 98195; and Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, Washington 98195.
Charles Timchalk*Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352; Texas Advanced Computing Center, University of Texas, Austin, Texas 78758; Radiology, University of Washington, Seattle, Washington 98195; and Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, Washington 98195.
Sudhakar Pipavath*Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352; Texas Advanced Computing Center, University of Texas, Austin, Texas 78758; Radiology, University of Washington, Seattle, Washington 98195; and Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, Washington 98195.
Robb Glenny*Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352; Texas Advanced Computing Center, University of Texas, Austin, Texas 78758; Radiology, University of Washington, Seattle, Washington 98195; and Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, Washington 98195.
Daniel R Einstein*Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352; Texas Advanced Computing Center, University of Texas, Austin, Texas 78758; Radiology, University of Washington, Seattle, Washington 98195; and Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, Washington 98195.
Pacific Northwest National Laboratory · USUniversity of Washington · USTexas Advanced Computing Center

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computational fluid dynamics (CFD) modeling is well suited for addressing species-specific anatomy and physiology in calculating respiratory tissue exposures to inhaled materials. In this study, we overcame prior CFD model limitations to demonstrate the importance of realistic, transient breathing patterns for predicting site-specific tissue dose. Specifically, extended airway CFD models of the rat and human were coupled with airway region-specific physiologically based pharmacokinetic (PBPK) tissue models to describe the kinetics of 3 reactive constituents of cigarette smoke: acrolein, acetaldehyde and formaldehyde. Simulations of aldehyde no-observed-adverse-effect levels for nasal toxicity in the rat were conducted until breath-by-breath tissue concentration profiles reached steady state. Human oral breathing simulations were conducted using representative aldehyde yields from cigarette smoke, measured puff ventilation profiles and numbers of cigarettes smoked per day. As with prior steady-state CFD/PBPK simulations, the anterior respiratory nasal epithelial tissues received the greatest initial uptake rates for each aldehyde in the rat. However, integrated time- and tissue depth-dependent area under the curve (AUC) concentrations were typically greater in the anterior dorsal olfactory epithelium using the more realistic transient breathing profiles. For human simulations, oral and laryngeal tissues received the highest local tissue dose with greater penetration to pulmonary tissues than predicted in the rat. Based upon lifetime average daily dose comparisons of tissue hot-spot AUCs (top 2.5% of surface area-normalized AUCs in each region) and numbers of cigarettes smoked/day, the order of concern for human exposures was acrolein > formaldehyde > acetaldehyde even though acetaldehyde yields were 10-fold greater than formaldehyde and acrolein.

Indexed as

Models, BiologicalSmokeAldehydesAnimalsHumansNicotianaRatsAldehydesSmokeacetaldehydeacroleinCFDcigarette smokeformaldehydePBPKrespiratory tractrisk assessment

Identifiers

PMID25858911
PMCPMC4476461
OpenAlexW2139614420

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.