Evidence map›Paper›PMID 42780353›Full record

ArticleEco-Environment & Health2026

Integrated risk prioritization of rubber additives based on hazard ranking and exposure characterization.

Sihan Wang, Wanting Dai, Bin Wang, Liping Heng

Abstract read
In one paragraph

Article in Eco-Environment & Health, 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

4 authors.

Sihan WangSchool of Chemistry, Beihang University, Beijing, 100191, China.
Wanting DaiSchool of Chemistry, Beihang University, Beijing, 100191, China.
Bin WangState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing, 100084, China.
Liping HengSchool of Chemistry, Beihang University, Beijing, 100191, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rubber products are widely used in transportation, construction, and electronics. At the same time, concern is growing over the environmental and human health risks of rubber additives. However, systematic screening is still limited because few workflows link hazard information with industrial formulation loading data. Here, we developed an integrated high-throughput screening workflow for rubber additives by harmonizing multiple authoritative databases to compile chemical structures, functional information, and representative formulation data. Multi-model and multi-endpoint quantitative structure-activity relationship (QSAR) predictions were integrated using two hazard-ranking strategies, and additional substances of concern were identified using criteria spanning persistence (P), bioaccumulation (B), mobility (M), and toxicity (T). Hazard-based screening identified 82 priority chemicals. For 12 specific rubber additives with publicly accessible formulation ranges, we further incorporated representative formulation loading and a molecular-weight-based migration potential metric. This step produced an exposure factor and an integrated Risk Index (RI). Under exposure-informed conditions, 2,2,4-trimethyl-1,2-dihydroquinoline (TMQ), N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD), and N-isopropyl-N'-phenyl-p-phenylenediamine (IPPD) were identified as top-priority additives by the integrated assessment. Overall, this framework improves the practical relevance of additive prioritization, thereby supporting greener material design, risk management, and substitution assessment in the rubber industry.

Indexed as

Formulation loadingMulti-model comparisonQSAR toolsRisk prioritizationRubber additives

Identifiers

PMID42780353
PMCPMC13597201

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.