Evidence map›Paper›PMID 26269405›Full record

ArticleThe Journal of investigative dermatology2015

Nanoparticles for Fidgety Cell Movement and Enhanced Wound Healing.

Ivan Jozic, Sylvia Daunert, Marjana Tomic-Canic, Irena Pastar

Abstract readComment
PubMed Publisher
In one paragraph

Article in The Journal of investigative dermatology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ivan JozicWound Healing and Regenerative Medicine Research Program, Department of Dermatology & Cutaneous Surgery, University of Miami Miller School of Medicine, Miami, Florida, USA.
Sylvia DaunertDepartment of Biochemistry and Molecular Biology, University of Miami Miller School of Medicine, Miami, Florida, USA; Dr JT Macdonald Biomedical Nanotechnology Institute, University of Miami, Miami, Florida, USA.
Marjana Tomic-CanicWound Healing and Regenerative Medicine Research Program, Department of Dermatology & Cutaneous Surgery, University of Miami Miller School of Medicine, Miami, Florida, USA.
Irena PastarWound Healing and Regenerative Medicine Research Program, Department of Dermatology & Cutaneous Surgery, University of Miami Miller School of Medicine, Miami, Florida, USA. Electronic address: IPastar@miami.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Complex spatiotemporal interaction of Rho GTPases with microtubules (MTs) and MT-associated proteins drives directed cellular migration. In this issue, Charafeddine et al. describe a role for a novel MT-severing enzyme, fidgetin-like 2 (FL2), in directional migration of keratinocytes and fibroblasts. FL2 normally localizes to the leading edge of the cell cortex where it shears MTs, thus dictating the size and distribution of focal adhesions by regulating cytoskeletal remodeling. Small interfering RNA (siRNA)-directed knockdown of FL2 increases cell migration and focal adhesion area in vitro through possible interaction with Rho GTPases. Efficient FL2 knockdown in murine wounds was achieved using nanoparticles as a siRNA delivery vehicle, and this resulted in enhanced wound closure in vivo. Effective siRNA nanoparticle targeting of MT-severing enzymes offers promise of controlled and targeted delivery that may maximize therapeutic success for patients with burn wounds and chronic wound disorders.

Indexed as

Adenosine TriphosphatasesAnimalsMicrotubulesNuclear ProteinsRNA, Small InterferingWound HealingWounds and InjuriesAdenosine TriphosphatasesNuclear ProteinsRNA, Small Interfering

Identifiers

PMID26269405

What OpenQuestion holds

Textmetadata
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.