Evidence map›Paper›PMID 42347427›Full record

ArticleToxics2026

In Silico Prediction of Chronic Oral Reference Doses for PIANO Target Analytes.

Paul D Rockswold, Gregory J Joseph, Elaine A Merrill, Christopher S Waldron, James S Smith

Abstract read
In one paragraph

Article in Toxics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Paul D RockswoldDefense Centers for Public Health, Portsmouth, VA 23708, USA.ORCID 0000-0002-5150-4976
Gregory J JosephDefense Centers for Public Health, Portsmouth, VA 23708, USA.
Elaine A MerrillNavy and Marine Corps Force Health Protection Command, Portsmouth, VA 23708, USA.ORCID 0000-0002-7751-0362
Christopher S WaldronPioneer Technologies Corporation, Olympia, WA 98503, USA.ORCID 0009-0007-1850-3887
James S SmithNavy and Marine Corps Force Health Protection Command, Portsmouth, VA 23708, USA.ORCID 0009-0003-2258-8327

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Characterizing the human health risk posed by constituents in drinking water is often challenging due to a lack of published toxicity values. The PIANO (Paraffin, Isoparaffin, Aromatic, Naphthene, and Olefin) analytical method measures nearly 300 compounds in JP-5 jet fuel, 43 of which have published oral reference doses (RfDs). The remaining compounds are typically assigned surrogate toxicity values. We predict RfDs for 290 PIANO compounds using Quantitative Structure-Activity Relationship (QSAR) models based on stepwise linear regression of 2-dimensional molecular descriptors (MDs) and published toxicity values. Five training groups, created by randomly selecting 80% of the non-PIANO compounds and 50% of the 43 PIANO compounds that have RfDs within a master dataset of 1113 compounds, were used to develop five QSAR models. We used the geometric means of four QSAR model results of sufficient quality to predict RfDs for compounds lacking toxicological information. For compounds with known RfDs, 884 (79%) were within 8-fold of published RfDs, well within the acknowledged uncertainty inherent in published RfDs. Our approach has applicability beyond PIANO compounds and represents a new alternative methodology (NAM) that may be used to reduce uncertainty in human health risk assessment and guide regulatory decisions.

Indexed as

chronic oral reference doses (RfDs)hydrocarbonsmolecular descriptorspetroleum compoundsquantitative structure–activity relationship (QSAR) modelsstepwise multivariable linear regression

Identifiers

PMID42347427
PMCPMC13308117

What OpenQuestion holds

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Registered trials

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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.