Evidence map›Paper›PMID 41273585›Full record

ArticleAdvances in experimental medicine and biology2026

Towards Precise Modelling of Diffusion Across the Blood-Brain Barrier.

Dimitrios Charemis, Gregory Sivolapenko, Maria Hadjinicolaou

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Article in Advances in experimental medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Dimitrios CharemisSchool of Science and Technology, Hellenic Open University, Patras, Greece. charemis.dimitris@ac.eap.gr.
Gregory SivolapenkoDepartment of Pharmacy, University of Patras, Patras, Greece.
Maria HadjinicolaouSchool of Science and Technology, Hellenic Open University, Patras, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this chapter, we outline the key components of modelling passive solute fluxes across the blood-brain barrier (BBB). An overview of BBB anatomy is provided, and physiological parameters at transport interfaces are quantified. We highlight the scarcity of approaches to passive diffusion that directly integrate biophysics into comprehensive differential models. To address this, we investigate solute transport dynamics at the BBB using a physiological model of parabolic partial differential equations (PDEs).Analytical and numerical solutions to our PDE system are obtained, and we use initial conditions to incorporate characteristic features of the transport process. Solute properties and BBB permeability values are considered in conjunction with appropriate boundary conditions. A PDE stability analysis is performed to ensure the model's accuracy and utility. We extend our investigation by directly comparing our PDE model to a semi-physiological, compartmental ODE model sourced from the literature.The convergence of temporal concentration values for mannitol and sucrose is demonstrated, and the inherent advantage of our PDE methodology in predicting spatial concentration values is outlined. The proposed PDE model offers unique computational advantages in studies of pharmaceutical targeting for neurological disorders: it can be further developed to model passive diffusion in both steady and unsteady states across multiple dimensions; it incorporates physiological and pharmaceutical parameters directly; and it provides both spatial and temporal predictions of solute diffusion across the BBB.

Indexed as

Blood-Brain BarrierModels, BiologicalAnimalsBiological TransportDiffusionHumansMannitolMannitolBlood-brain barrier (BBB)Drug targetingPartial differential equations (PDEs)Passive diffusionTransport modelling

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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.