Evidence map›Paper›PMID 35880683›Full record

ReviewWIREs mechanisms of disease2023

Computational models for generating microvascular structures: Investigations beyond medical imaging resolution.

Cameron Apeldoorn, Soroush Safaei, Julian Paton, Gonzalo D Maso Talou

Abstract readReview
In one paragraph

Review in WIREs mechanisms of disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
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.

Cameron ApeldoornAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.ORCID 0000-0003-3618-2945
Soroush SafaeiAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.ORCID 0000-0001-5734-243X
Julian PatonCardiovascular Autonomic Research Cluster, Department of Physiology, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.ORCID 0000-0001-7410-2913
Gonzalo D Maso TalouAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.ORCID 0000-0002-5208-992X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Angiogenesis, arteriogenesis, and pruning are revascularization processes essential to our natural vascular development and adaptation, as well as central players in the onset and development of pathologies such as tumoral growth and stroke recovery. Computational modeling allows for repeatable experimentation and exploration of these complex biological processes. In this review, we provide an introduction to the biological understanding of the vascular adaptation processes of sprouting angiogenesis, intussusceptive angiogenesis, anastomosis, pruning, and arteriogenesis, discussing some of the more significant contributions made to the computational modeling of these processes. Each computational model represents a theoretical framework for how biology functions, and with rises in computing power and study of the problem these frameworks become more accurate and complete. We highlight physiological, pathological, and technological applications that can be benefit from the advances performed by these models, and we also identify which elements of the biology are underexplored in the current state-of-the-art computational models. This article is categorized under: Cancer > Computational Models Cardiovascular Diseases > Computational Models.

Indexed as

Diagnostic ImagingNeovascularization, PhysiologicComputer SimulationRadiographyangiogenesisarteriogenesiscancercomputational modelpruning

Identifiers

PMID35880683
PMCPMC10077909

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.