Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Modelling approach in cell/material interactions studies.

Karine Anselme1, Maxence Bigerelle

  • 1Institut de Chimie des Surfaces et Interfaces (ICSI), UPR CNRS 9069, 15 rue Jean Starcky, BP2488, 68057 Mulhouse Cedex, France. Karine.Anselme@uha.fr

Biomaterials
|November 1, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The O‑GlcNAcase Inhibition by Thiamet G Disrupts the AngioMatrix Signature of the Glioblastoma Secretome In Silico and Impairs Its Angiogenic Capacity In Vitro.

Journal of molecular biology·2026
Same author

Surface Inspection and Description in Metrology and Tribology-Vol. 2.

Materials (Basel, Switzerland)·2026
Same author

Multiscale and re-entrant surface analysis of multi jet fusion surfaces and the effect of postprocessing via sandblasting.

Scientific reports·2025
Same author

Breast implant silicone exposure induces immunogenic response and autoimmune markers in human periprosthetic tissue.

Biomaterials·2024
Same author

Fabrication and characterization of thin self-rolling film for anti-inflammatory drug delivery.

Colloids and surfaces. B, Biointerfaces·2024
Same author

Two 3D Fractal-Based Approaches for Topographical Characterization: Richardson Patchwork versus Sdr.

Materials (Basel, Switzerland)·2024
Same journal

Remodeling TME via feedback-driven photothermal-ferroptosis-immune cascade.

Biomaterials·2026
Same journal

Corrigendum to "Photodynamic therapy produces enhanced efficacy of antitumor immunotherapy by simultaneously inducing intratumoral release of sorafenib" [Biomaterials 2020, 240, 119845].

Biomaterials·2026
Same journal

Mg-integrated octopus-inspired hydrogel dressing enables autonomous adhesion and wound closure for enhanced healing via sequential microenvironment regulation.

Biomaterials·2026
Same journal

Engineering miRNA-223 nanocomplexes via bioorthogonal self-assembly for precision therapy of intervertebral disc degeneration.

Biomaterials·2026
Same journal

Corrigendum to "Enhanced fluorescence imaging guided photodynamic therapy of sinoporphyrin sodium loaded graphene oxide" [Biomaterials 42 (2015) 16442].

Biomaterials·2026
Same journal

An injectable Ce-MnCo LDH nanozyme gel with cascade catalytic activity for acute radiation proctitis in rats.

Biomaterials·2026
See all related articles

This study introduces a statistical modeling approach for analyzing in vitro cell/material interactions. It details experimental design and employs bootstrap methods to identify key parameters influencing these interactions.

Area of Science:

  • Biomaterials Science
  • Statistical Modeling
  • Cell Biology

Background:

  • Understanding in vitro cell/material interactions is crucial for biomaterial development.
  • Current experimental approaches may not fully capture the complexity of multiple interacting parameters.

Purpose of the Study:

  • To propose a statistical modeling framework for in vitro cell/material interactions.
  • To provide principles for designing experiments that allow comprehensive modeling.
  • To illustrate the application of statistical techniques, like bootstrapping, in analyzing cell/material interaction data.

Main Methods:

  • Experimental design for comprehensive cell/material interaction studies.
  • Application of the bootstrap protocol for data amplification and correlation elimination.

Related Experiment Videos

  • Identification of the most relevant parameters using statistical analysis.

    • Main Results:

    • Demonstration of essential features for modeling cell/material interactions.
    • Illustration of bootstrap protocol applications in parameter analysis.
    • Quantification of the relative influence of biological and physical parameters.

    Conclusions:

    • Statistical modeling, particularly using bootstrap methods, is effective for analyzing complex cell/material interactions.
    • The proposed approach aids in designing more ambitious experiments with multiple parameters.
    • This framework enhances the understanding of factors governing cell-material interactions in biomaterial research.