Search research articles

Related Concept Videos

Mechanisms of Membrane-bending

Mechanisms of Membrane-bending

The living membranes are flexible due to their fluid mosaic nature; however, their bending into different shapes is an active process regulated by specific lipids and proteins. The membrane bending can be transient as seen in vesicles or stable for a long time as in microvilli. Cells regulate the size, location, and duration of the membrane curvature.
Membrane bending can happen due to intrinsic changes in lipid composition or extrinsic association with different proteins. The proteins involved...

You might also read

Related Articles

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

Sort by

Same author

An ankyrin G-binding motif mediates TRAAK periodic localization at axon initial segments of hippocampal pyramidal neurons.

Proceedings of the National Academy of Sciences of the United States of America·2024

Same author

Decreased number of colonic tuft cells in quiescent ulcerative colitis patients.

European journal of gastroenterology & hepatology·2020

Same author

Altered Structural Expression and Enzymatic Activity Parameters in Quiescent Ulcerative Colitis: Are These Potential Normalization Criteria?

International journal of molecular sciences·2020

Same author

Intense Activity of the Raphe Spinal Pathway Depresses Motor Activity via a Serotonin Dependent Mechanism.

Frontiers in neural circuits·2018

Same author

The DLGAP family: neuronal expression, function and role in brain disorders.

Molecular brain·2017

Same author

Monoclonal Antibodies Follow Distinct Aggregation Pathways During Production-Relevant Acidic Incubation and Neutralization.

Pharmaceutical research·2015

Same journal

ASCT: a pipeline for standardized analysis of MEG/EEG directional connectivity. Practical guidelines for applications of source-based Directed Transfer Function.

Frontiers in neuroinformatics·2026

Same journal

Predicting vasovagal syncope during head-up tilt test: three machine learning approaches.

Frontiers in neuroinformatics·2026

Same journal

Decoding basal ganglia motor circuit dysfunction from handwriting: a physics-informed neural signal interpretation framework for Parkinson's disease screening.

Frontiers in neuroinformatics·2026

Same journal

FUSION-AD: interpretable AI framework for risk assessment and subgroup discovery in Alzheimer's disease.

Frontiers in neuroinformatics·2026

Same journal

A 3D-printed phantom to validate subject orientation in 3D imaging and recordings.

Frontiers in neuroinformatics·2026

Same journal

IntegriLAB: a blockchain-enabled electronic lab notebook for reproducible neuroimaging research.

Frontiers in neuroinformatics·2026

See all related articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Jan 18, 2026

Measuring Properties of the Membrane Periodic Skeleton of the Axon Initial Segment using 3D-Structured Illumination Microscopy 3D-SIM

Measuring Properties of the Membrane Periodic Skeleton of the Axon Initial Segment using 3D-Structured Illumination Microscopy 3D-SIM

Published on: February 11, 2022

A correlation-based tool for quantifying membrane periodic skeleton associated periodicity.

Sam K Vanspauwen¹, Virginia Luque-Fernández¹, Hanne B Rasmussen¹

¹Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

Frontiers in Neuroinformatics

|September 8, 2025

Summary

This summary is machine-generated.

We developed Napari-WaveBreaker, an open-source tool to quantify the periodic localization of proteins within the membrane-associated periodic skeleton (MPS). This method accurately analyzes MPS periodicity and co-distribution, aiding in understanding neuronal structure.

Keywords:

autocorrelation axon initial segment cross-correlation membrane-associated periodic skeleton napari software super-resolution microscopy

More Related Videos

Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles

Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles

Published on: October 15, 2014

Molecular Spring Constant Analysis by Biomembrane Force Probe Spectroscopy

Molecular Spring Constant Analysis by Biomembrane Force Probe Spectroscopy

Published on: November 20, 2021

Related Experiment Videos

Last Updated: Jan 18, 2026

Measuring Properties of the Membrane Periodic Skeleton of the Axon Initial Segment using 3D-Structured Illumination Microscopy 3D-SIM

Measuring Properties of the Membrane Periodic Skeleton of the Axon Initial Segment using 3D-Structured Illumination Microscopy 3D-SIM

Published on: February 11, 2022

Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles

Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles

Published on: October 15, 2014

Molecular Spring Constant Analysis by Biomembrane Force Probe Spectroscopy

Molecular Spring Constant Analysis by Biomembrane Force Probe Spectroscopy

Published on: November 20, 2021

Area of Science:

Neuroscience
Cell Biology
Biophysics

Background:

Super-resolution microscopy revealed the membrane-associated periodic skeleton (MPS), a neuronal cytoskeletal structure with actin rings spaced 190 nm apart.
Numerous proteins associate with the MPS, but tools for quantifying their periodic localization are limited.

Purpose of the Study:

To develop an open-source tool for accurate and unbiased quantification of MPS periodicity and protein co-distribution.
To provide a framework for analyzing molecular organization within the MPS.

Main Methods:

Development of Napari-WaveBreaker, an open-source plugin for the Napari image viewer.
Utilized autocorrelation to quantify MPS periodicity and cross-correlation for assessing co-distribution of targets.
Evaluated performance using simulated datasets and STED microscopy images.

Main Results:

Napari-WaveBreaker accurately quantified MPS periodicity and detected spatial shifts between periodic targets.
The tool demonstrated robustness across varying image qualities.
Successfully distinguished between periodic and non-periodic protein distributions.

Conclusions:

Napari-WaveBreaker offers an unbiased, quantitative framework for analyzing MPS periodicity and co-distribution.
Enables new insights into the molecular organization and modulation of the MPS.