Evidence map›Paper›PMID 39050784›Full record

ArticleComputational and structural biotechnology journal2024

Advancing PFAS risk assessment: Integrative approaches using agent-based modelling and physiologically-based kinetic for environmental and health safety.

Martina Iulini, Giulia Russo, Elena Crispino, Alicia Paini, Styliani Fragki, Emanuela Corsini, Francesco Pappalardo

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. ARACRA: Automated RNA-seq Analysis for Chemical Risk Assessment.Computational and structural biotechnology journal · 2026
    Article
  2. Review
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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

7 authors.

Martina IuliniUniversità degli Studi di Milano, Department of Pharmacology and Biomolecular Sciences 'Rodolfo Paoletti', Milan, Italy.
Giulia RussoUniversity of Catania, Department of Drug and Health Sciences, Italy.
Elena CrispinoUniversity of Catania, Department of Biomedical and Biotechnological Sciences, Italy.
Alicia PainiesqLABS GmbH, Saterland, Germany.
Styliani FragkiesqLABS GmbH, Saterland, Germany.
Emanuela CorsiniUniversità degli Studi di Milano, Department of Pharmacology and Biomolecular Sciences 'Rodolfo Paoletti', Milan, Italy.
Francesco PappalardoUniversity of Catania, Department of Drug and Health Sciences, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Per- and polyfluoroalkyl substances (PFAS), ubiquitous in a myriad of consumer and industrial products, and depending on the doses of exposure represent a hazard to both environmental and public health, owing to their persistent, mobile, and bio accumulative properties. These substances exhibit long half-lives in humans and can induce potential immunotoxic effects at low exposure levels, sparking growing concerns. While the European Food Safety Authority (EFSA) has assessed the risk to human health related to the presence of PFAS in food, in which a reduced antibody response to vaccination in infants was considered as the most critical human health effect, a comprehensive grasp of the molecular mechanisms spearheading PFAS-induced immunotoxicity is yet to be attained. Leveraging modern computational tools, including the Agent-Based Model (ABM) Universal Immune System Simulator (UISS) and Physiologically Based Kinetic (PBK) models, a deeper insight into the complex mechanisms of PFAS was sought. The adapted UISS serves as a vital tool in chemical risk assessments, simulating the host immune system's reactions to diverse stimuli and monitoring biological entities within specific adverse health contexts. In tandem, PBK models unravelling PFAS' biokinetics within the body i.e. absorption, distribution, metabolism, and elimination, facilitating the development of time-concentration profiles from birth to 75 years at varied dosage levels, thereby enhancing UISS-TOX's predictive abilities. The integrated use of these computational frameworks shows promises in leveraging new scientific evidence to support risk assessments of PFAS. This innovative approach not only allowed to bridge existing data gaps but also unveiled complex mechanisms and the identification of unanticipated dynamics, potentially guiding more informed risk assessments, regulatory decisions, and associated risk mitigations measures for the future.

Indexed as

Agent-based modelingImmunotoxicityPer- and polyfluoroalkyl substances (PFAS)Physiologically based kinetic modelingRisk assessment

Identifiers

PMID39050784
PMCPMC11267999

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.