Evidence map›Paper›PMID 24527361›Full record

ArticleAdvances in wound care2013

A Network Approach to Wound Healing.

Tomasz Arodz, Danail Bonchev, Robert F Diegelmann

Abstract read
In one paragraph

Article in Advances in wound care, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Transcriptional changes in human palate and skin healing.Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. The gestational power of mast cells in the injured tissue.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2018
    Review
  9. Article
  10. Article
  11. Review
  12. GHK and DNA: resetting the human genome to health.BioMed research international · 2014
    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

3 authors.

Tomasz ArodzDepartment of Computer Science, Virginia Commonwealth University , Richmond, Virginia. ; VCU Reanimation, Engineering, and Science Center, Virginia Commonwealth University , Richmond, Virginia.
Danail BonchevVCU Reanimation, Engineering, and Science Center, Virginia Commonwealth University , Richmond, Virginia. ; Center for the Study of Biological Complexity, Virginia Commonwealth University , Richmond, Virginia.
Robert F DiegelmannVCU Reanimation, Engineering, and Science Center, Virginia Commonwealth University , Richmond, Virginia. ; Department of Biochemistry & Molecular Biology, Virginia Commonwealth University , Richmond, Virginia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe wound healing process is well-understood on the cellular and tissue level; however, its complex molecular mechanisms are not yet uncovered in their entirety. Viewing wounds as perturbed molecular networks provides the tools for analyzing and optimizing the healing process. It helps to answer specific questions that lead to better understanding of the complexity of the process. What are the molecular pathways involved in wound healing? How do these pathways interact with each other during the different stages of wound healing? Is it possible to grasp the entire mechanism of regulatory interactions in the healing of a wound? APPROACH: Networks are structures composed of nodes connected by links. A network describing the state of a cell taking part in the healing process may contain nodes representing genes, proteins, microRNAs, metabolites, and drug molecules. The links connecting nodes represent interactions such as binding, regulation, co-expression, chemical reaction, and others. Both nodes and links can be weighted by numbers related to molecular concentration and the intensity of intermolecular interactions. Proceeding from data and from molecular profiling experiments, different types of networks are built to characterize the stages of the healing process. Network nodes having a higher degree of connectivity and centrality usually play more important roles for the functioning of the system they describe.

resultsWe describe here the algorithms and software packages for building, manipulating and analyzing networks proceeding from information available from a literature or database search or directly extracted from experimental gene expression, metabolic, and proteomic data. Network analysis identifies genes/proteins most differentiated during the healing process, and their organization in functional pathways or modules, and their distribution into gene ontology categories of biological processes, molecular functions, and cellular localization. We provide an example of how network analysis can be used to reach better understanding of regulation of key wound healing mediators and microRNAs that regulate them. INNOVATION: Univariate statistical tests widely used in clinical studies are not enough to improve understanding and optimize the processes of wound healing. Network methods of analysis of patients "omics" data, such as transcriptoms, proteomes, and others can provide a better insight into the healing processes and help in development of better treatment practices. We review several articles that are examples of this emergent approach to the study of wound healing.

conclusionNetwork analysis has the potential to considerably contribute to the better understanding of the molecular mechanisms of wound healing and to the discovery of means to control and optimize that process.

Identifiers

PMID24527361
PMCPMC3816993

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Registered trials

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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.