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Record W4407243220 · doi:10.1055/s-0045-1803679

Histological Factors Contributing to the Viscoelasticity of Intracranial Meningiomas Analyzed by Atomic Force Microscopy

2025· article· en· W4407243220 on OpenAlexaff
Juliette Fournier-Loiselle, Théophraste Lescot, Stéphan Saïkali, Martin Côté, Marc‐André Fortin, Pierre‐Olivier Champagne

Bibliographic record

VenueJournal of Neurological Surgery Part B Skull Base · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsViscoelasticityAtomic force microscopyMeningiomaMedicineMaterials sciencePathologyComposite materialNanotechnology

Abstract

fetched live from OpenAlex

Objective: The consistency of a meningioma is a determining factor in the ease of resection, particularly in relation to critical structures such as vessels and cranial nerves. A better understanding of the histologic factors that affect meningioma’s viscoelasticity is needed to help predict their consistency. This study aims to identify the histological determinants of meningioma viscoelasticity measured by atomic force microscopy. Materials and Methods: This is a prospective study using meningioma specimens from a tumor bank. All adults’ intracranial meningiomas that have not undergone embolization or radiation were included. The median viscoelasticity obtained by atomic force microscopy for each meningioma was correlated to the collagen percentage, with Masson’s trichrome stain; the vascularity percentage, with CD31 as a marker for endothelial cells; and the mean cellularity, assessed by counting cells in a 400× field. The viscoelasticity was calculated using the Hertz modulus: where F is the force, E is the Young modulus, μ is the Poisson’s ratio, R is the cantilever’s radius, and δ the indentation depth. Meningiomas’ viscoelasticity obtained with atomic force microscopy was correlated with clinical data, including intraoperative complications, extent of surgical resection and progression-free-survival. Statistical analysis was conducted using linear regression and logistic regression. Results: Twenty-two tumors were analyzed in these preliminary results. The mean surface area of the meningiomas was 23,64 mm 2 . The mean elasticity for all tumors was 5.871 kPa (0.483–23.882 kPa). The mean cellularity was 4103 cells/mm 2 (2,272–6867 cells/mm 2 ). The mean percentage of vascularity was 41.7% (10–90%) and of collagen w,as 41% (5–90%). No strong correlation was found, but vascularity appears to have a low negative correlation with viscoelasticity ([ Fig. 1 ]). Fig. 1 Correlation between mean vascularity and the median viscoelasticity for each meningioma. WHO grade 2 meningiomas had a median viscoelasticity significantly lower than WHO grade 1 (2.516 kPa vs. 6.858 kPa, p = 0.043). Conclusion: WHO grade 2 meningiomas tend to be softer than grade 1. More meningiomas need to be studied to find a strong correlation between prognosis or histological determinants and viscoelasticity. Publication History Article published online: 07 February 2025 © 2025. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.276
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
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