Evidence map›Paper›PMID 41940407›Full record

ArticleEngineering with computers2026

A computational framework to predict the spreading of Alzheimer's disease.

Ana Vazquez-Palomo, Covadonga Betegón, Johannes Weickenmeier, Emilio Martínez-Pañeda

Abstract read
In one paragraph

Article in Engineering with computers, 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
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0citing papers in PubMed
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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

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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.

Ana Vazquez-PalomoDepartment of Construction and Manufacturing Engineering, University of Oviedo, Gijón, 33203 Spain.
Covadonga BetegónDepartment of Construction and Manufacturing Engineering, University of Oviedo, Gijón, 33203 Spain.
Johannes WeickenmeierDepartment of Engineering Science, University of Oxford, Oxford, OX1 3PJ UK.
Emilio Martínez-PañedaDepartment of Engineering Science, University of Oxford, Oxford, OX1 3PJ UK.

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI Duygu Tosun-Turgut · 2016 to 2026
$226.7M
NIA NIH HHS U19 AG024904
6 · The paper itself

Abstract

Alzheimer's disease is characterised by the spreading of misfolded proteins and progressive structural changes in the brain. Despite significant clinical research, understanding how microscopic protein dynamics translate into macroscopic tissue degeneration remains a major challenge. In this work, we present a three-dimensional, finite element-based computational framework to model disease progression by combining multi-protein transport and brain tissue deformation within anatomically realistic geometries. The propagation of toxic tau and amyloid-[Formula: see text] proteins is described using reaction-diffusion equations of the Fisher-Kolmogorov type, incorporating prion-like growth mechanisms and anisotropic transport along white matter fibre tracts. Brain atrophy is represented through a hyperelastic constitutive model driven by protein-dependent volume loss. Subject-specific simulations are achieved through an automated preprocessing pipeline that generates finite element meshes and reconstructs axonal orientation fields from medical imaging data. The model reproduces key morphological patterns observed in Alzheimer's disease and shows good quantitative agreement with longitudinal imaging measurements. Overall, the proposed framework offers an extensible computational platform for studying Alzheimer's disease progression across subject-specific brain geometries. The models developed, including the image processing framework (BrainImage2Mesh) and the coupled bio-chemo-mechanical COMSOL finite element implementation, are made freely available to download at https://mechmat.web.ox.ac.uk/codes. Supplementary Information: The online version contains supplementary material available at 10.1007/s00366-026-02313-5.

Indexed as

Alzheimer’s diseaseBio-chemo-mechanical modellingBrain multi-physicsCerebral atrophyFinite element modelling

Identifiers

PMID41940407
PMCPMC13043544

What OpenQuestion holds

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LicenceCC BY
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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.