Evidence map›Paper›PMID 28939878›Full record

ArticleScientific reports2017

Immunophysical analysis of corneal neovascularization: mechanistic insights and implications for pharmacotherapy.

Youness Azimzade, Jiaxu Hong, Alireza Mashaghi

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Collagen as a Biomaterial for Skin and Corneal Wound Healing.Journal of functional biomaterials · 2022
    Review
  3. Article
  4. Review
  5. 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 at 1 institution in 1 country.

Youness AzimzadeLeiden Academic Centre for Drug Research, Faculty of Mathematics and Natural Sciences, Leiden University, Leiden, The Netherlands.
Jiaxu HongLeiden Academic Centre for Drug Research, Faculty of Mathematics and Natural Sciences, Leiden University, Leiden, The Netherlands.
Alireza MashaghiLeiden Academic Centre for Drug Research, Faculty of Mathematics and Natural Sciences, Leiden University, Leiden, The Netherlands. a.mashaghi.tabari@lacdr.leidenuniv.nl.
Leiden University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The cornea lacks adaptive immune cells and vasculature under healthy conditions, but is populated by both cell types under pathologic conditions and after transplantation. Here we propose an immunophysical approach to describe postoperative neovascularization in corneal grafts. We develop a simple dynamic model that captures not only the well-established interactions between innate immunity and vascular dynamics but also incorporates the contributions of adaptive immunity to vascular growth. We study how these interactions determine dynamic changes and steady states of the system as well as the clinical outcome, i.e. graft survival. The model allows us to systematically explore the impact of pharmacological inhibitors of vascular growth on the function and survival of transplanted corneas and search for the optimal time to initiatetherapy. Predictions from our models will help ongoing efforts to design therapeutic approaches to modulate alloimmunity and suppress allograft rejection.

Indexed as

Models, BiologicalAdaptive ImmunityAllograftsCorneaCorneal NeovascularizationCorneal TransplantationGraft RejectionHumansImmunosuppressive AgentsPostoperative ComplicationsImmunosuppressive Agents

Identifiers

PMID28939878
PMCPMC5610330
OpenAlexW2755748040

What OpenQuestion 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 OpenQuestion graph.