Evidence map›Paper›PMID 41878011›Full record

ArticleFrontiers in toxicology2026

Zhuangyan Monica Xu, James P Sluka, Charlie C Zhang, Gregory Knipp

Erratum issuedAbstract read
In one paragraph

Article in Frontiers in toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

4 authors.

Zhuangyan Monica XuDepartment of Industrial and Molecular Pharmaceutics, College of Pharmacy, Purdue University, West Lafayette, IN, United States.
James P SlukaBiocomplexity Institute, Intelligent Systems Engineering, Indiana University, Bloomington, IN, United States.
Charlie C ZhangDepartment of Industrial and Molecular Pharmaceutics, College of Pharmacy, Purdue University, West Lafayette, IN, United States.
Gregory KnippDepartment of Industrial and Molecular Pharmaceutics, College of Pharmacy, Purdue University, West Lafayette, IN, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Neurotoxicity is a critical liability for many environmental pollutants. Current in vitro neurotoxicity screens rely on direct exposure of cultured neurons to xenobiotics, often at exceeding physiologically relevant levels due to the restrictive nature of the blood -brain barrier (BBB). This limitation reduces the accuracy of central nervous system (CNS) exposure predictions. Methods: To address this limitation, we have developed a novel human in vitro direct-contact triculture BBB model that more closely mimics the in vivo barrier. The triculture is formed by layering primary astrocytes, primary pericytes, and then brain microvessel endothelial cells (BMECs, HBEC-5i) in direct contact, increasing the restrictive nature of tight junctions and allowing cell -cell signaling that mimics the configuration found in the in vivo BBB. Using this model, we quantified the apparent bidirectional permeability (P Results: The triculture model demonstrated enhanced tight junction organization and increased efflux transporter expression compared with endothelial monocultures, indicating an improved barrier phenotype. Using our measured bidirectional Papp values, calculated efflux ratios, and EPA physiologically based pharmacokinetic (PBTK) reference data for compound parameters, we are developing predictions of toxicant accumulation in the brain parenchyma after chronic exposure in steady state. Discussion: Integration of

Indexed as

apparent permeabilityblood-brain barrierCNS exposure predictionefflux ratiohigh throughput toxicokinetics in RHTTK-Rin vitro-in vivoIVIVE

Identifiers

PMID41878011
PMCPMC13008315

What Socratic holds

Textmetadata
LicenceCC BY
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.