Evidence map›Paper›PMID 24527362›Full record

ArticleAdvances in wound care2013

Computational Modeling of Inflammation and Wound Healing.

Cordelia Ziraldo, Qi Mi, Gary An, Yoram Vodovotz

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 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
5.8field-weighted citation impact, top 5% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.

  1. Pooled it
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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

4 authors at 2 institutions in 1 country.

Cordelia ZiraldoCenter for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh , Pittsburgh, Pennsylvania. ; Department of Computational and Systems Biology, University of Pittsburgh , Pittsburgh, Pennsylvania.
Qi MiCenter for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh , Pittsburgh, Pennsylvania. ; Department of Sports Medicine and Nutrition, University of Pittsburgh , Pittsburgh, Pennsylvania.
Gary AnDepartment of Surgery, University of Chicago , Chicago, Illinois.
Yoram VodovotzCenter for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh , Pittsburgh, Pennsylvania. ; Department of Surgery, University of Pittsburgh , Pittsburgh, Pennsylvania.
University of Pittsburgh · USUniversity of Chicago · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveInflammation is both central to proper wound healing and a key driver of chronic tissue injury via a positive-feedback loop incited by incidental cell damage. We seek to derive actionable insights into the role of inflammation in wound healing in order to improve outcomes for individual patients. APPROACH: To date, dynamic computational models have been used to study the time evolution of inflammation in wound healing. Emerging clinical data on histo-pathological and macroscopic images of evolving wounds, as well as noninvasive measures of blood flow, suggested the need for tissue-realistic, agent-based, and hybrid mechanistic computational simulations of inflammation and wound healing. INNOVATION: We developed a computational modeling system, Simple Platform for Agent-based Representation of Knowledge, to facilitate the construction of tissue-realistic models.

resultsA hybrid equation-agent-based model (ABM) of pressure ulcer formation in both spinal cord-injured and -uninjured patients was used to identify control points that reduce stress caused by tissue ischemia/reperfusion. An ABM of arterial restenosis revealed new dynamics of cell migration during neointimal hyperplasia that match histological features, but contradict the currently prevailing mechanistic hypothesis. ABMs of vocal fold inflammation were used to predict inflammatory trajectories in individuals, possibly allowing for personalized treatment.

conclusionsThe intertwined inflammatory and wound healing responses can be modeled computationally to make predictions in individuals, simulate therapies, and gain mechanistic insights.

Identifiers

PMID24527362
PMCPMC3816782
OpenAlexW2128135511

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.