Evidence map›Paper›PMID 27015595›Full record

ArticleCytoskeleton (Hoboken, N.J.)2016

A spatiotemporal characterization method for the dynamic cytoskeleton.

Ghada Alhussein, Aya Shanti, Ilyas A H Farhat, Sara B H Timraz, Noaf S A Alwahab, Yanthe E Pearson, Matthew N Martin, Nicolas Christoforou, Jeremy C M Teo

Open access · hybridAbstract read
In one paragraph

Article in Cytoskeleton (Hoboken, N.J.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.5field-weighted citation impact, top 20% of its field
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

10 citing papers in PubMed, 19 citations in OpenAlex.

  1. Review
  2. Review
  3. Quantifying cytoskeletal organization from optical microscopy data.Frontiers in cell and developmental biology · 2023
    Review
  4. Article
  5. Article
  6. Biomedical potential of mammalian spectraplakin proteins: Progress and prospect.Experimental biology and medicine (Maywood, N.J.) · 2019
    Review
  7. Article
  8. Review
  9. Article
  10. 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

9 authors at 2 institutions in 2 countries.

Ghada AlhusseinDepartment of Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates.
Aya ShantiDepartment of Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates.
Ilyas A H FarhatDepartment of Applied Mathematics and Sciences, Khalifa University, Abu Dhabi, United Arab Emirates.
Sara B H TimrazDepartment of Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates.
Noaf S A AlwahabSchool of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Yanthe E PearsonDepartment of Applied Mathematics and Sciences, Khalifa University, Abu Dhabi, United Arab Emirates.
Matthew N MartinDepartment of Applied Mathematics and Sciences, Khalifa University, Abu Dhabi, United Arab Emirates.
Nicolas ChristoforouDepartment of Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates.
Jeremy C M TeoDepartment of Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates.
Khalifa University of Science and Technology · AEÉcole Polytechnique Fédérale de Lausanne · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The significant gap between quantitative and qualitative understanding of cytoskeletal function is a pressing problem; microscopy and labeling techniques have improved qualitative investigations of localized cytoskeleton behavior, whereas quantitative analyses of whole cell cytoskeleton networks remain challenging. Here we present a method that accurately quantifies cytoskeleton dynamics. Our approach digitally subdivides cytoskeleton images using interrogation windows, within which box-counting is used to infer a fractal dimension (Df ) to characterize spatial arrangement, and gray value intensity (GVI) to determine actin density. A partitioning algorithm further obtains cytoskeleton characteristics from the perinuclear, cytosolic, and periphery cellular regions. We validated our measurement approach on Cytochalasin-treated cells using transgenically modified dermal fibroblast cells expressing fluorescent actin cytoskeletons. This method differentiates between normal and chemically disrupted actin networks, and quantifies rates of cytoskeletal degradation. Furthermore, GVI distributions were found to be inversely proportional to Df , having several biophysical implications for cytoskeleton formation/degradation. We additionally demonstrated detection sensitivity of differences in Df and GVI for cells seeded on substrates with varying degrees of stiffness, and coated with different attachment proteins. This general approach can be further implemented to gain insights on dynamic growth, disruption, and structure of the cytoskeleton (and other complex biological morphology) due to biological, chemical, or physical stimuli. © 2016 Wiley Periodicals, Inc.

Indexed as

ActinsCytoskeletonDermisFibroblastsHumansMicroscopy, FluorescenceActinscytoskeleton rearrangementhigh-throughput analysislive-imagingmechanobiologytemporal analysis

Identifiers

PMID27015595
PMCPMC5132051
OpenAlexW2308131526

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.